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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
Sun Oct 01 2023
Journal Name
Optical Fiber Technology
A taper-in-etch based hybrid fiber Mach-Zehnder interferometer hydrogen sensor
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid Framework To Exclude Similar and Faulty Test Cases In Regression Testing
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Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

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Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials &amp; Continua
A New Hybrid Feature Selection Method Using T-test and Fitness Function
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Publication Date
Fri Dec 24 2021
Journal Name
Journal Of Engineering Science And Technology. Journal Of Engineering Science And Technology
Grey-Level Image Compression Using 1-D Polynomial and Hybrid Encoding Techniques
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
A Comparative Study of Single-Constraint Routing in Wireless Mesh Networks Using Different Dynamic Programming Algorithms
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Finding the shortest route in wireless mesh networks is an important aspect. Many techniques are used to solve this problem like dynamic programming, evolutionary algorithms, weighted-sum techniques, and others. In this paper, we use dynamic programming techniques to find the shortest path in wireless mesh networks due to their generality, reduction of complexity and facilitation of numerical computation, simplicity in incorporating constraints, and their onformity to the stochastic nature of some problems. The routing problem is a multi-objective optimization problem with some constraints such as path capacity and end-to-end delay. Single-constraint routing problems and solutions using Dijkstra, Bellman-Ford, and Floyd-Warshall algorith

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Publication Date
Tue Dec 01 2009
Journal Name
2009 7th International Conference On Information, Communications And Signal Processing (icics)
The effect of traffic load on using XCAST based routing protocol in wireless ad hoc networks
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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Overlapping Structure Detection in Protein-Protein Interaction Networks Using a Modified Version of Particle Swarm Optimization
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In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Artificial Neural Networks Modeling of Total Dissolved Solid in the Selected Locations on Tigris River, Iraq
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Automated Detection of Dubas Bug Infestation in Palm Trees Using Deep Learning with Residual Neural Networks
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Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Impact of Denial-of-Service Attack on Directional Compact Geographic Forwarding Routing Protocol in Wireless Sensor Networks
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Directional Compact Geographic Forwarding (DCGF) routing protocol promises a minimal overhead generation by utilizing a smart antenna and Quality of Service (QoS) aware aggregation. However, DCGF was tested only in the attack-free scenario without involving the security elements. Therefore, an investigation was conducted to examine the routing protocol algorithm whether it is secure against attack-based networks in the presence of Denial-of-Service (DoS) attack. This analysis on DoS attack was carried out using a single optimal attacker, A1, to investigate the impact of DoS attack on DCGF in a communication link. The study showed that DCGF does not perform efficiently in terms of packet delivery ratio and energy consumption even on a sin

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