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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
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Mon May 20 2019
Journal Name
Journal Of Planner And Development
THE EVALUATION OF PUBLIC SERVICES IN BAQUBAH CITY BY USING REMOTE SENSING & GIS TECHNIQUES
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Baqubah city has grown extremely rapidly. The rate of growth exceeds the growth of services that must grow side by side with the growth of population. There are natural features that affect the growth of Baqubah city such as Dieyala river, Alssariya river, in addition to agricultural areas .All these natural features affect the growth of Baqubah city in the running form being seen . In this research the remote sensing and geographic information system (GIS) techniques are used for monitoring urban expansion and forecasting the probable axes to the growth of the city, and found that the probability of Baqubah growth to east is preferred due to Baqubah growth to the east would never interfere with natural features. Also in this res

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Mechanisms of Plant-Correlation Phytoremediation of Al-Daura Iraqi Refinery Wastewater Using Wetland Plant from Tigris River
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In developing countries, conventional physico-chemical methods are commonly used for removing contaminants. These methods are not efficient and very costly. However, new in site strategy with high treatment efficiency and low operation cost named constructed wetland (CW) has been set. In this study, Phragmites australis was used with free surface batch system to estimate its ability to remediate total
petroleum hydrocarbons (TPH) and chemical oxygen demand (COD) from Al-Daura refinery wastewater. The system operated in semi-batch, thus, new wastewater was weekly added to the plant for 42 days. The results showed high removal percentages (98%) of TPH and (62.3%) for COD. Additionally, Phragmites australis biomass increased significant

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Publication Date
Wed May 10 2017
Journal Name
Journal Of The College Of Languages (jcl)
Die literarische Übersetzung und Deutlichkeit dem Leser Literary Translation and Receive Manifestation
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Die Forschung geht  um das wichtigste Thema für die literarischen Studien, die um die literarische Übersetzung und die Deutlichkeit dem Leser gekreist sind. Die literarische Übersetzung ist ein schwieriger Prozess, der auf vielseitigen Faktoren beruht ist, damit es erfolgreich gelungen ist. Dies ist auch ein gemeinsamer Prozess durch das Kunstwerk zwischen dem Autor und Übersetzer, so dass der erste Schritt in der vorliegenden Forschung wie folgendes lautet: muss es der Autor genau bestimmt wird, wie er die methodischen Grundprinzipien des Wekes im Dienst der zentralen Idee formuliert, und wie er die literarische Gestalt durch die voll erfassende Vorstellung des Wekes dichtet. Denn die literarische Arbeit besteht aus zwei Teilen

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment And Total Dissolved Solids Prediction For Tigris River In Baghdad City Using Mathematical Models
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Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

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Publication Date
Tue Dec 01 2020
Journal Name
Iraqi Journal Of Physics
Water Quality Assessment for Tigris River Through Salah Al-Din Province, Iraq Using Remote Sensing Techniques
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water quality assessment is still being done at specific locations of major concern. The use of Geographical Information System (GIS) based water quality information system and spatial analysis with Inverse Distance Weighted interpolation enabled the mapping of water quality indicators along Tigris river in Salah Al-Din government, Iraq. Water quality indicators were monitored by taking 13 river samples from different locations along the river during Winter season year 2020. Maps of 10 water quality indicators. This meant that the specific water quality indicator and diffuse pollution characteristics in the basin were better illustrated with the variations displayed along the course of the river than conventional line graphs. Creation of

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
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Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p> ... Show More
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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Tue Oct 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
AUTOMATIC ARABIC KEYWORD EXTRACTION USING LOGISTIC REGRESSION
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