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Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>

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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
An Investigation into the Behavior of Disc Blake Wear
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A real method of predication brake pad wear ,could lead to substantiol economies of time and money. This paper describes how such a procedure has been used and gives the results to establish is reliability by comparing the predicted wear with that which actually occurs in an existing service. The experimental work was carried out on three different commercial samples ,tested under different operation conditions (speed,load,time...etc)using a test ring especially modified for this purpose. Abrasive wear is mainly studied , since it is the type of wear that takes place in such arrangements. Samples wear tested in presences of sand or mud between the mating surfaces under different operational conditions of speed, load and braking time .Mec

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Internal Marketing on Organizational Citizenship Behavior
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The aim of this paper is to determine the effect of internal marketing through three dimensions: vision, development, and reward - on organizational citizenship behavior in three private universities in Iraq. Organizations’ view of their members as internal customers could be made them more realistic in dealing with the reasons for leaving and going to other organizations. This can promote business organizations to build an organizational environment that contributes to making the organization look like the homeland of those workers. The research method is descriptive and analytical. The tool for data collection was the questionnaire. Statistical software (SPSS V.23 and AMOS V.23) was used to analyze the data. The research sample was r

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
The Behavior of Gypseous Soil under Vertical Vibration Loading
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The dynamic response of foundation rest on collapsible soil in dry and soaked states is studied through wide experimental programmed. Gypseous soil from Tikrit governorate area was obtained and subjected to various physical and chemical analysis to determine its properties. Steel rectangular footing (400x200x20) mm is manufactured. The machine is fitted to the footing, then the model machine foundation is placed centrally over the prepared soil layer in steel container (1200x 1000x1000)mm with proper care to maintain the center of gravity of whole system lie in the same vertical line with container.Then, the footing is subjected to vertical harmonic loading using a rotating mass type mechanical oscillator to simulate different dynamic lo

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Publication Date
Thu Jan 30 2020
Journal Name
Telecommunication Systems
Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends
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Publication Date
Mon Jan 28 2019
Journal Name
Soft Computing
Bio-inspired multi-objective algorithms for connected set K-covers problem in wireless sensor networks
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Publication Date
Fri Dec 14 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Diabetes Self-Management among Patients in Baghdad City: A Comparative Study
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Objective(s): To Evaluate Diabetes self –management among patients in Baghdad City and to compare
between these patients self-management relative to the type of the disease.
Methodology: A descriptive design was conducted in Baghdad city, started from November 16th 2017 to the
end of May 17 th 2018 in order to evaluate Diabetes self-management. Purposive (non-probability) sample,
which was consisted of (120) patients who were diagnosed with D.M. The sample is comprised of (60) patient
with diabetes type I and (60) patient with diabetes type II. It is consisted of (60) male and (60) female. A
questionnaire is constructed for the purpose of the study. It is composed of (42) items. Reliability and validity of
the ques

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Composites For Construction
Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Composites For Construction
Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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