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Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
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Publication Date
Tue Dec 26 2017
Journal Name
International Journal Of Science And Research (ijsr)
Investigating the Effect of Using Waste Glass on the Properties of Asphalt Concrete Wearing Course Mixture
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The reuse or recycling of waste materials in different aspects of life is served the objective of sustainability and be beneficial to society. In recent years, a wide variety of waste materials were used in pavement construction. One of these materials is glass that generally produces in large quantities and crushed glass can be considered feasible alternative source of aggregate for asphalt mixture production. This study focused on examining the asphalt mixture properties of wearing course using crushed glass as fine aggregates. Fine crushed glass with various percentages by total weight retained on sieve 2.36 mm, 0.3 mm and 0.075 mm was used in the study. The results indicate that mixes containing crushed glass had lower Marshall stabilit

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Publication Date
Wed Oct 18 2023
Journal Name
Ieee Access
A New Imputation Technique Based a Multi-Spike Neural Network to Handle Missing Data in the Internet of Things Network (IoT)
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Publication Date
Sun Mar 30 2003
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Active Alumina Extraction from Iraqi Bauxite for Catalyst's Support
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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Physics: Conference Series
Neural Network Model for Synthesis of Thermally Sprayed (AI/AI<sub>2</sub>O<sub>3</sub>) Composite Protective Coatings
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Abstract<p>Al<sub>2</sub>O<sub>3</sub> and Al<sub>2</sub>O<sub>3</sub>–Al composite coatings were deposited on steel specimens using Oxy-acetylene gas thermal spray gun. Alumina was mixed with Aluminum in six groups of concentrations (0, 5, 10,12,15 and 20% ) Al2O3, Specimens were tested for corrosion using Potentiodynamic polarization technique. Further tests were conducted for the effect of temperature on polarization curve and the hardness tests for the coated specimens. At first, Modelling was carried out using MINITAB-19, least square method, as a 2nd degree nonlinear model, bad results were achieved because of the high nonlinearity. Better result w</p> ... Show More
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Publication Date
Mon Feb 19 2018
Journal Name
Al-academy
Balanced performance and structural mechanisms in industrial product design systems
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The research focused on (balanced performance and structural mechanisms in industrial product design systems) by focusing on product development in a manner that is able to meet the human requirements through the effect of smart technology on the systems of product designs and its effectiveness in achieving the design and functional variables that have an effective effect in User and industrial products, correspond to the requirements of the user life at the level of daily interaction. The first chapter ensures the problem of research is the following question: What are the mechanisms to achieve balanced performance in some systems design to fit with the variables B N User and industrial products? The objective of the research was to ide

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Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Mobile Position Estimation based on Three Angles of Arrival using an Interpolative Neural Network
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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
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Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Scopus (16)
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