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Utilizing Soft Computing Techniques to Estimate the Axial Permanent Deformation of Asphalt Concrete
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Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R2 of 0.93 and a mean squared error (MSE) of 0.0039. Results based on the sensitivity analysis and variable importance techniques showed that the percentage of aggregate passing the 4.75 mm sieve and the (rice) theoretical maximum specific gravity (Gmm) were the most significant factors in predicting axial permanent strain (εp). Furthermore, the connection weight method highlighted input variables’ distinct positive and negative impacts on permanent deformation.

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Towards Perceptions building a descriptive and procedural for the knowledge assets at the center of learning and growth for the techniques of Balanced Score card in the light of the strategic map concepts to achieve the strategic and operational: requirements of the contemporary business
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Abstract:

   Witness the current business environment changes rapidly reflected on the performance of the facility wishing to stay , which is no longer style reaction enough to handle installations with their environment , and quickly began to lose its luster with the emergence of a message and the vision of contemporary business environment from a set of parts interacting with each other and the concept of behavioral includes all dimensions of performance, it is imperative to adopt a system installations influence variables and positive interaction through the development of strategic plans and the use of implementation and follow-up strategies to ensure the effectiveness of the method for meas

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Publication Date
Mon Feb 07 2022
Journal Name
Innovative Infrastructure Solutions
Chemical and rheological properties of reclaimed asphalt binders modified by waste engine oil
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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
RHEOLOGICAL PROPERTIES OF IRAQI ASPHALT BINDERS MEASURED USING SUPERPAVE SYSTEM AND SHELL SOFTWARE
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The performance grading system (superpave) has provided means to incorporate binder characteristics with
pavement failure types. It’s a comprehensive system that relates climate, traffic conditions and aging with
critical pavement distress. The objective of this paper is to develop an improved asphalt binder grading
system for Iraq based on the principal of superpave. The country was divided into different zones according
to the highest and lowest temperature ranges and traffic loading. The Performance graded binder proposed
for each zone was compared with some States of USA that have same hot weather of Iraq by using Long
Term Pavement Performance (LTPP v3.1) software. Iraqi asphalt samples were tested using the Supe

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Publication Date
Tue Sep 19 2017
Journal Name
International Journal Of Science And Research
Volumetric Change of Concrete Containing Water Absorption Polymer Balls
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Polymers have the ability to extract water after they have been added to the mortar or concrete mixture. They provide the absorbed water during hydration functioning as internal water source. Absorption polymers can absorb up to hundred times of their own weight of pure water.This research deals with the use of water absorption polymer balls in concrete and study the volumetric change of these mixes and compared the results with reference mix (without polymers). Samples were cured both in air and in water for the mixes to compare results which show that samples in air behave for expansion while sample in water acted for shrinkage.

Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
PROPERTIES OF HARDENED CONCRETE USING CRUSHED CLAY BRICK AS AGGREGATES
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This paper provides the result of an investigation to use of crushed clay brick as
aggregates in producing concrete. Eight different crushed clay brick aggregate concretes were
used in this investigation. Compressive strength, splitting tensile strength and pulse velocity of
crushed clay brick aggregates concrete were determined and compare to natural aggregate
concrete. The compressive strength of crushed clay brick aggregates concretes were always
lower than the compressive strength of natural aggregates concrete regardless the age of
concrete, but the crushed clay brick aggregates concrete showed better performance as the age of
concrete increases and average reduction in compressive strength were 33.5% at the age

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Publication Date
Wed Apr 30 2025
Journal Name
Iraqi Journal Of Science
Numerical Simulation of Solar Granulation Dynamics Using Optical Correction Techniques
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High-resolution imaging of celestial bodies, especially the sun, is essential for understanding dynamic phenomena and surface details. However, the Earth's atmospheric turbulence distorts the incoming light wavefront, which poses a challenge for accurate solar imaging. Solar granulation, the formation of granules and intergranular lanes on the sun's surface, is important for studying solar activity. This paper investigates the impact of atmospheric turbulence-induced wavefront distortions on solar granule imaging and evaluates, both visually and statistically, the effectiveness of Zonal Adaptive Optics (AO) systems in correcting these distortions. Utilizing cellular automata for granulation modelling and Zonal AO correction methods,

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Sun Dec 30 2018
Journal Name
Baghdad Science Journal
Geomorphological Mapping of Razzaza–Habbaria Area using Remote Sensing Techniques
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Landforms on the earth surface are so expensive to map or monitor. Remote Sensing observations from space platforms provide a synoptic view of terrain on images. Satellite multispectral data have an advantage in that the image data in various bands can be subjected to digital enhancement techniques for highlighting contrasts in objects for improving image interpretability. Geomorphological mapping involves the partitioning of the terrain into conceptual spatial entities based upon criteria. This paper illustrates how geomorphometry and mapping approaches can be used to produce geomorphological information related to the land surface, landforms and geomorphic systems. Remote Sensing application at Razzaza–Habbaria area southwest of Razz

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Publication Date
Mon Sep 03 2018
Journal Name
Al-academy
Transformer Technician in Pop Art (Study in techniques of show)
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The popular art movement emerged in the mid-fifties in Britain in parallel with its appearance in America.. It was linked to contemporary social reality and what distinguishes this art is the most sophisticated and less aesthetic means and the most blatant in the field of media, ie back to the image used in the media, journalism, magazines, television and photo Which reflect the reality of the neutral artist. This research included the methodological framework represented by the research problem that emerged from pop art as a new experimental vision that emerged in the twentieth century and the importance of the research and its objectives and limits and the definition of terms. The theoretical framework dealt with evolution Technology,

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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