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Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international information network has showed that the error rate in the training and the testing process was about (10%) and that the results of the network query has given the results of acceptable accuracy statistically so that it was better than results obtained from multiple linear regression equation for the same data.

 

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Publication Date
Tue Aug 22 2017
Journal Name
Heat Transfer—asian Research
Thermal Enhancement from Pin Fins by Using Elliptical Perforations with Different Inclination Angles
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Abstract<p>Many of the proposed methods introduce the perforated fin with the straight direction to improve the thermal performance of the heat sink. The innovative form of the perforated fin (with inclination angles) was considered. Present rectangular pin fins consist of elliptical perforations with two models and two cases. The signum function is used for modeling the opposite and the mutable approach of the heat transfer area. To find the general solution, the degenerate hypergeometric equation was used as a new derivative method and then solved by Kummer's series. Two validation methods (previous work and Ansys 16.0‐Steady State Thermal) are considered. The strong agreement of the validation results (0.3</p> ... Show More
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Publication Date
Sat Dec 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Chromium (VI) Removal from Wastewater by Electrocoagulation Process Using Taguchi Method: Batch Experiments
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Electrocoagulation is an electrochemical method for treatment of different types of wastewater  whereby sacrificial anodes corrode to release active coagulant (usually aluminium or iron cations) into solution, while simultaneous evolution of hydrogen at the cathode allows for pollutant removal by flotation or settling. The Taguchi method was applied as an experimental design and to determine the best conditions for chromium (VI) removal from wastewater. Various parameters in a batch stirred tank by iron metal electrodes: pH, initial chromium concentration, current density, distance between electrodes and KCl concentration were investigated, and the results have been analyzed using signal-to-noise (S/N) ratio. It was found that the r

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Publication Date
Sat Mar 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reinforcement Steel Corrosion Reduction by Using Fly Ash from South Baghdad Power Plant
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Corrosion- induced damage in reinforced concrete structure such as bridges, parking garages, and buildings, and the related cost for maintaining them in a serviceable condition, is a source of major concern for the owners of these structures.
Fly ash produced from south Baghdad power plant with different concentrations (20, 25 and 30) % by weight from the cement ratio were used as a corrosion inhibitor as a weight ratio from the cement content.
The concrete batch ratio under study was (1:1.5:3) cement, sand and gravel respectively which is used in Iraq. All the raw materials used were locally manufactured.
Concrete slabs (250x250x70) mm dimensions were casted, using Poly-wood molds. Two steel bars were embedded in the central po

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Publication Date
Fri Sep 01 2017
Journal Name
Al-nahrain Journal Of Science
Study of Charge Density Distributions and Elastic Charge Form Factors for 40Ca and 48Ca
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The ground charge density distributions (CDD), elastic charge form factors and proton, charge, neutron, and matter root mean square (rms) radii for stable 40Ca and 48Ca have been calculated using single-particle radial wave functions of Woods-Saxon (WS) and harmonic-oscillator (HO) potentials. Different central potential depths are used for each subshell which is adjusted so as to reproduce the experimental single-nucleon binding energies. An excellent agreement between the calculated rms charge radii and experimental data are found for both nuclei using WS and HO potentials. The calculated proton rms radii for 40Ca are found to be in good agreement with experiment data using both WS and HO potentials while the results for 48Ca showed an ov

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Publication Date
Sun Dec 01 2019
Journal Name
Al-nahrain Journal Of Science
Enhancing Sparse Adjacency Matrix for Community Detection in Large Networks
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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
Simple 2D chaotic remapping scheme for securing optical communication networks
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In this work, a simple and new method is proposed to simultaneously improve the physical layer security and the transmission performance of the optical orthogonal frequency division multiplexing system, by combining orthogonal frequency division multiplexing technique with chaotic theory principles. In the system, a 2-D chaotic map is employed. The introduced system replaces complex operations such as matrix multiplication with simple operations such as multiplexing and inverting. The system performance in terms of bit error rate (BER) and peak to average ratio (PAPR) is enhanced. The system is simulated using Optisystem15 with a MATLAB2016 and for different constellations. The simulation results showed that the  BE

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A Developed Colorimetric Assay Using Unmodified Gold Nanoparticles for the Identification of Acinetobacter baumannii Isolates from Different Clinical Samples
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  Acinetobacter baumannii (A. baumannii ) is considered a critical healthcare problem for patients in intensive care units due to its high ability to be multidrug-resistant to most commercially available antibiotics. The aim of this study is to develop a colorimetric assay to quantitatively detect the target DNA of A. baumannii based on unmodified gold nanoparticles (AuNPs) from different clinical samples (burns, surgical wounds, sputum, blood and urine). A total of thirty-six A. baumannii clinical isolates were collected from five Iraqi hospitals in Erbil and Mosul provinces within the period from September 2020 to January 2021. Bacterial isolation and biochemical identification of isolates

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Silver nanoparticles synthesized by three species of genus Streptococcus and evaluate their synergistic effects with the oil extracted from Syzygium Aromaticum on some clinical bacterial isolates
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Silver nanoparticles synthesized by different species

Publication Date
Thu Jun 23 2022
Journal Name
American Scientific Research Journal For Engineering, Technology, And Sciences
A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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