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Extraction Drainage Network for Lesser Zab River Basin from DEM using Model Builder in GIS
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ArcHydro is a model developed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. Raster-based digital elevation models (DEMs) play an important role in distributed hydrologic modeling supported by geographic information systems (GIS). Digital Elevation Model (DEM) data have been used to derive hydrological features, which serve as inputs to various models. Currently, elevation data are available from several major sources and at different spatial resolutions. Detailed delineation of drainage networks is the first step for many natural resource management studies. Compared with interpretation from aerial photographs or topographic maps, automation of drainage network extraction from DEMs is an efficient way and has received considerable attention. This study aims to extract drainage networks from Digital Elevation Model (DEM) for Lesser Zab River Basin. Composition parameters of the drainage network including the numbers of streams and the stream lengths are derived from the DEM beside the delineation of catchment areas in the basin. The results from this application can be used to create input files for many hydrologic models.

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Study of the Biological Diversity of Benthic algae in the Tigris River, Baghdad - Iraq
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Abstract<p>The present work included a study of benthic algae on two substrates: rocks and clay on a section of the Tigris River at the Al-Atifiyah site in the fall of 2018. The result of this study was recorded 89 species belong to 50 genus of benthic algae on both substrates and composed of Bacillariophyceae (59.6%, 61.2%), Chlorophyceae (25.8%, 20.4%) and Cyanophyceae (14.5%, 18.3%) respectively on epilithic and epipelic algae. The present study was recorded the highest total algae cell density (1173.2 cells *10<sup>3</sup>/cm<sup>2</sup>) on epilithic algae while the lowest total algae cell density was recorded on epipelic algae (76.95 cells *10<sup>3</sup>/gm). For measure div</p> ... Show More
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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Water Resource And Protection
Seasonal Variations of Some Ecological Parameters in Tigris River Water at Baghdad Region, Iraq
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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Qualitative and Quantitative study of Epipelic algae in Tigris River within Baghdad City, Iraq
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The present study conducted to study epipelic algae in the Tigris River within Baghdad city for one year from September 2011 to August 2012 due to the importance role of benthic algae in lotic ecosystems. Five sites have been chosen along the river. A total of 154 species of epipelic algae was recorded belongs to 45 genera, where Bacillariophyceae (Diatoms) was the dominant groups followed by Cyanophyceae and Chlorophyceae. The numbers of common types in three sites were 47 species. Bacillariophyceae accounted 88.31% of the total number of epipelic algae, followed by Cyanophyceae 7.14 % and Chlorophyceae 4.55%. A 85 species (29 genera) recorded in site 1, 103 species (34 genera) in site2, 112 species (35 genera) in site3, 96 species

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Publication Date
Sun Jun 03 2018
Journal Name
Baghdad Science Journal
Diversity Measurement Indices of Diatom Communities in the Tigris River within Wasit Province, Iraq
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The study was conducted to measure diatom species diversity in the lotic ecosystem across the Wasit Province for 12 months. The quantitative study of diatoms (phytoplankton) was investigated in the Tigris river. The density of algae was ranged from 60989 cell×103/l to 112780.82 cell×103/l in the five sites. These algae were belonging to 39 genera. The richness index values ranged from 1.53 at site 5 in January 2016 to 6.34 at site 1 and June2015. Shannon-Weiner diversity index (H´) was 2.33 in February 2016 and 3.72 in June 2015 both values at site 3, whereas Evenness index was 0.54 at site 5 in March2016 and 0.98 at site 1 in both August2015 and May2016. The lack of homogeneity of the appearance of species indicates the dominance of a

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Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6
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The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

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Publication Date
Mon Oct 01 2018
Journal Name
Ieee Transactions On Network Science And Engineering
A Resource Allocation Mechanism for Cloud Radio Access Network Based on Cell Differentiation and Integration Concept
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Publication Date
Sat Jun 01 2019
Journal Name
2019 International Symposium On Networks, Computers And Communications (isncc)
An Interference Mitigation Scheme for Millimetre Wave Heterogeneous Cloud Radio Access Network with Dynamic RRH Clustering
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Comparison of HF and HCl Chemical Laser Parameters by using Mathematical Model
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A simplified theoretical comparison of the hydrogen chloride (HCl) and hydrogen fluoride (HF) chemical lasers is presented by using computer program. The program is able to predict quantitative variations of the laser characteristics as a function of rotational and vibrational quantum number. Lasing is assumed to occur in a Fabry-Perot cavity on vibration-rotation transitions between two vibrational levels of hypothetical diatomic molecule. This study include a comprehensive parametric analysis that indicates that the large rotational constant of HF laser in comparison with HCl laser makes it relatively easy to satisfy the partial inversion criterion. The results of this computer program proved their credibility when compared with th

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