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Proposing a Scheme for Human Interactive Proof Test using Plasma Effect
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            Human Interactive Proofs (HIPs) are automatic inverse Turing tests, which are intended to differentiate between people and malicious computer programs. The mission of making good HIP system is a challenging issue, since the resultant HIP must be secure against attacks and in the same time it must be practical for humans. Text-based HIPs is one of the most popular HIPs types. It exploits the capability of humans to recite text images more than Optical Character Recognition (OCR), but the current text-based HIPs are not well-matched with rapid development of computer vision techniques, since they are either vey simply passed or very hard to resolve, thus this motivate that continuous efforts are required to improve the development of HIPs base text. In this paper, a new proposed scheme is designed for animated text-based HIP; this scheme exploits the gap between the usual perception of human and the ability of computer to mimic this perception and to achieve more secured and more human usable HIP. This scheme could prevent attacks since it's hard for the machine to distinguish characters with animation environment displayed by digital video, but it's certainly still easy and practical to be used by humans because humans are attuned to perceiving motion easily. The proposed scheme has been tested by many Optical Character Recognition applications, and it overtakes all these tests successfully and it achieves a high usability rate of 95%.

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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
Mon Sep 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Phenolic Compounds from Aqueous Solution by Using Agricultural Waste (Al-Khriet)
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Adsorption techniques are widely used to remove organics pollutants from waste water particularly, when using low cost adsorbent available in Iraq. Al-Khriet powder which was found in legs of Typha Domingensis is used as bio sorbent for removing phenolic compounds from aqueous solution. The influence of adsorbent dosage and contact time on removal percentage and adsorb ate amount of phenol and 4- nitro phenol onto Al-Khriet were studied. The highest adsorption capacity was for 4-nitrophenol 91.5% than for phenol 82% with 50 mg/L concentration, 0.5 gm. dosage of adsorbent and pH 6 under a batch condition. The experimental data were tested using different isotherm models. The results show that Freundlich model resulted in the best fit also

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Enhancement of Iraqi Light Naphtha Octane Number Using Pt Supported HMOR Zeolite Catalyst
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The hydroconversion of Iraqi light straight run naphtha was studied on zeolite catalyst. 0.3wt.%Pt/HMOR catalyst was prepared locally and used in the present work. The hydroconversion performed on a continuous fixed-bed laboratory reaction unit. Experiments were performed in the temperature range of 200 to 350°C, pressure range of 3 to 15 bars, LHSV range of 0.5-2.5h-1, and the hydrogen to naphtha ratio of 300.

The results show that the hydroconversion of Iraqi light straight naphtha increases with increase in reaction temperature and decreases with increase in LHSV.

High octane number isomers were formed at low temperature of 240°C. The selectivity of hydroisomerization improved by increasing reaction pressu

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

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Publication Date
Sat Sep 01 2018
Journal Name
2018 15th European Radar Conference (eurad)
Delamination Detection in Glass-Fibre Reinforced Polymer (GFRP) Using Microwave Time Domain Reflectometry
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Publication Date
Sat Jun 26 2021
Journal Name
Asian Journal Of Civil Engineering
Using AHP to prioritize the corruption risk practices in the Iraqi construction sector
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Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Physics: Conference Series
Green synthesis of gold NPs by using dragon fruit: Toxicity and wound healing
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Abstract<p>In this work, the study of <italic>Hylocereus undatus</italic> properties was done by studying quantitative phytochemical compounds and seeking for total phenolic compounds, synthesis of gold nanoparticles was created via reduction of aqueous gold ions with the aqueous fruit extract of The <italic>Hylocereus undatus</italic> (dragon). The synthesized AuNPs were asserted by using (Uv-Vis) spectrophotometer; Fourier transforms infrared (FI-IR) spectroscopy, Atomic force microscope (AFM), Scanning Electron Microscopy (SEM) Zitasizer. The absorbance for SPR is noticed in 546 nm by using Uv-Visible spectroscopy The SEM and AFM analysis evidenced the particle size betwee</p> ... Show More
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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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