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joe-1822
Evaluating Roads Network Connectivity for Two Municipalities in Baghdad-Iraq
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The road network serves as a hub for opportunities in production and consumption, resource extraction, and social cohabitation. In turn, this promotes a higher standard of living and the expansion of cities. This research explores the road network's spatial connectedness and its effects on travel and urban form in the Al-Kadhimiya and Al-Adhamiya municipalities. Satellite images and paper maps have been employed to extract information on the existing road network, including their kinds, conditions, density, and lengths. The spatial structure of the road network was then generated using the ArcGIS software environment. The road pattern connectivity was evaluated using graph theory indices. The study demands the abstraction and examination of the topological structure by choosing a few factors associated with the connection of the roads. These involved the cyclomatic number, Eta coefficient, Aggregate Transform Score (ATS), Beta, gamma, and Alpha indices. According to the findings, the Al-Adhamiya roads network is more developed, better linked, and has a higher overall connectivity value than the Al-Kadhimiya network. The two study areas, however, have minimal circuitry and high complexity. Due to the modifications and expansion of land use that the municipalities have seen, the research suggests that the transportation network should be developed to reach greater interconnectedness, particularly in locations outside the city center.

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Publication Date
Mon Jul 01 2013
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
RAILLIETINA ECHINOBOTHRIDA (MEGNIN,1881) (CESTODA: CYCLOPHYLLIDEA) FROM THE HOUSE SPARROW PASSER DOMESTICUS BIBLICUS HARTRET, 1881 COLLECTED IN BAGHDAD CITY, CENTRAL IRAQ
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    The widespread house sparrow Passer domesticus biblicus has a close association with humans and  inhabits almost all ecosystems near human settlements in Iraq. It is exposed to different kinds of parasites in its habitats. Examining of house sparrow for the cestode parasites revealed that 25 specimens of 56 were infected with Raillietina echinobothrida. Intensity among infected male and female hosts with this cestode and its description  is provided and discussed. The present finding constitutes the first record for this parasite in house sparrow in Iraq.

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Publication Date
Mon Dec 30 2024
Journal Name
Cumhuriyet Üniversitesi Fen-edebiyat Fakültesi Sosyal Bilimler Dergisi
French Language in Iraq: Study of the Relationship between University Education and Social Activities (The Case of the University of Baghdad)
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Cumhuriyet Üniversitesi Fen-Edebiyat Fakültesi Sosyal Bilimler Dergisi | Volume: 48 Issue: 2

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Publication Date
Sun Nov 10 2019
Journal Name
Journal Of Engineering And Applied Sciences
Discrete Fracture Network and Fractured Reservoir Characterization in Khabaz Field-Tertiary Formation
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Publication Date
Sat Dec 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Dynamic Virtual Network Embedding with Latency Constraint in Flex-Grid Optical Networks
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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating the strategic performance of agricultural projects by adopting international indicators
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The aim of this research is to test the relationship of influence and correlation between strategic performance and its five dimensions (financial dimension, after internal processes, after internal customer satisfaction, after learning and growth, environmental and social dimension), by adopting international indicators in agricultural projects To determine the extent of the differences between the research variable and its dimensions, and then try to come out with a number of recommendations that contribute to the evaluation of agricultural projects and their performance by diagnosing and treating deviations, and based on the importance of the research topic in agricultural institutions. Institutions of the Environment and Soci

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Publication Date
Sun Dec 01 2024
Journal Name
Nordic Concrete Research
Evaluating Concrete Strength Under Various Curing Conditions Using Artificial Neural Networks
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Abstract<p>This study examines the impact of different curing methods on the compressive strength of concrete. It investigates techniques such as air curing, periodic water spraying, full water submersion, and polyethylene encasement. Artificial neural network models were employed to evaluate the compressive strength under each curing condition. A model for calculating compressive strength that considers surrounding conditions was created using an artificial neural network. The current study’s figures were generated using this model. The research thoroughly examined the impact of curing environments and concrete mix components on strength properties, taking into account factors such as tempera</p> ... Show More
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Publication Date
Mon Sep 30 2013
Journal Name
International Journal Of Network Security &amp; Its Applications
Evaluating the Performance of the Secure Block Permutation Image Steganography Algorithm
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Recently, a new secure steganography algorithm has been proposed, namely, the secure Block Permutation Image Steganography (BPIS) algorithm. The new algorithm consists of five main steps, these are: convert the secret message to a binary sequence, divide the binary sequence into blocks, permute each block using a key-based randomly generated permutation, concatenate the permuted blocks forming a permuted binary sequence, and then utilize a plane-based Least-Significant-Bit (LSB) approach to embed the permuted binary sequence into BMP image file format. The performance of algorithm was given a preliminary evaluation through estimating the PSNR (Peak Signal-to-Noise Ratio) of the stego image for limited number of experiments comprised hiding

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