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Turbid of Water By Using Fuzzy C- Means and Hard K- Means
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In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

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Publication Date
Sat Aug 31 2019
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Improvement of Economic Water Productivity of Cucumber by using Soil Water Retention Technology under Subsurface Trickle Irrigation System
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Subsurface soil water retention (SWRT) is a recent technology for increasing the crop yield, water use efficiency and then the water productivity with less amount of applied water. The goal of this research was to evaluate the existing of SWRT with the influence of surface and subsurface trickle irrigation on economic water productivity of cucumber crop. Field study was carried out at the Hawr Rajab district of Baghdad governorate from October 1st, to December 31st, 2017. Three experimental treatments were used, treatment plot T1 using SWRT with subsurface trickle irrigation, plot T2 using SWRT with surface trickle irrigation, while plot T3 without using SWRT and using surface tickle irrigation system. The obtained results showed th

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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 Apr 01 2026
Journal Name
Case Studies In Construction Materials
Performance Evaluation of Modified Hard-Grade Asphalt Binder Using Waste PVC Derived from Flex Banners
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Hard-grade asphalt binders, such as AC 20–30, offer excellent resistance to permanent deformation but are inherently brittle, making them highly susceptible to fatigue and low-temperature cracking. While polymer modification addresses these issues, virgin polymers remain expensive. Despite the growing interest in recycled plastics, the rheological impact of complex waste streams, specifically polyvinyl chloride (PVC) derived from flex banners containing plasticizers, on excessively stiff binders within the complete Superpave Performance Grading (PG) framework remains critically underexplored. This study introduces a novel valorization approach by utilizing solvent-extracted flex banner waste (WPVC) as a dual-action modifier. It leverages

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Maximum Likelihood Method And Bayesian Method For Estimating Some Non-Homogeneous Poisson Processes Models
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Abstract

The Non - Homogeneous Poisson  process is considered  as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).

This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto ,   to estimate th

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Publication Date
Mon Feb 01 2021
Journal Name
Neuroquantology
Study and Investigation of Hard Photons Emission in Heavy Ion Collisions
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This work involves hard photon rate production from quark -gluon plasma QGP interaction in heavy ion collision. Using a quantum chromodynamic model to investigate and calculation of photons rate in 𝑐𝑔 → 𝑠𝑔𝛾 system due to strength coupling, photons rate, temperature of system, flavor number and critical. The photons rate production computed using the perturbative strength models for QGP interactions. The strength coupling was function of temperature of system, flavor number and critical temperature. Its influenced by force with temperature of system, its increased with decreased the temperature and vice versa. The strength coupling has used to examine the confinement and deconfinement of quarks in QGP properties and inf

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between the empirical bayes method with moments method to estimate the affiliation parameter in the clinical trials using simulation
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In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Removal of Water Turbidity by using Aluminum Filings as a Filter Media
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The ability of using aluminum filings which is locally solid waste was tested as a mono media in gravity rapid filter. The present study was conducted to evaluate the effect of variation of influent water turbidity (10, 20and 30 NTU); flow rate(30, 40, and 60 l/hr) and bed height (30and60)cm on the performance of aluminum filings filter media for 5 hours run time and compare it with the conventional sand filter. The results indicated that aluminum filings filter showed better performance than sand filter in the removal of turbidity and in the reduction of head loss. Results showed that the statistical model developed by the multiple linear regression was proved to be
valid, and it could be used to predict head loss in aluminum filings

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Publication Date
Mon May 20 2019
Journal Name
Journal Of Planner And Development
THE EVALUATION OF PUBLIC SERVICES IN BAQUBAH CITY BY USING REMOTE SENSING & GIS TECHNIQUES
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Baqubah city has grown extremely rapidly. The rate of growth exceeds the growth of services that must grow side by side with the growth of population. There are natural features that affect the growth of Baqubah city such as Dieyala river, Alssariya river, in addition to agricultural areas .All these natural features affect the growth of Baqubah city in the running form being seen . In this research the remote sensing and geographic information system (GIS) techniques are used for monitoring urban expansion and forecasting the probable axes to the growth of the city, and found that the probability of Baqubah growth to east is preferred due to Baqubah growth to the east would never interfere with natural features. Also in this res

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Using the Elzaki decomposition method to solve nonlinear fractional differential equations with the Caputo-Fabrizio fractional operator
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The techniques of fractional calculus are applied successfully in many branches of science and engineering, one of the techniques is the Elzaki Adomian decomposition method (EADM), which researchers did not study with the fractional derivative of Caputo Fabrizio. This work aims to study the Elzaki Adomian decomposition method (EADM) to solve fractional differential equations with the Caputo-Fabrizio derivative. We presented the algorithm of this method with the CF operator and discussed its convergence by using the method of the Cauchy series then, the method has applied to solve Burger, heat-like, and, couped Burger equations with the Caputo -Fabrizio operator. To conclude the method was convergent and effective for solving this type of

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