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Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five attributes of the training process. The results of the second experiment showed improvement in the performance of the KNN and the Multilayer Perceptron. The results of the second experiment showed a slight decrease in the performance of the Random Forest with 97.5 % accuracy.

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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology (jatit)
Factors and Model for Sensitive Data Management and Protection in Information Systems’ Decision of Cloud Environment
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Journal of Theoretical and Applied Information Technology is a peer-reviewed electronic research papers & review papers journal with aim of promoting and publishing original high quality research dealing with theoretical and scientific aspects in all disciplines of IT (Informaiton Technology

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
Choosing Appropriate Distribution ‏‎by Minitab’s 17 Software to Analysis System Reliability
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This research aims to choose the appropriate  probability ‎ distribution  ‎‏‎ to the reliability‎        analysis‎ for  an   item through ‎ collected data for operating and stoppage  time of  the case  study.

    Appropriate choice for .probability distribution   is when  the data look to be on or  close the form fitting line for probability plot and test the data  for  goodness of fit .

     Minitab’s 17 software  was used ‎  for this  purpose after  arranging collected data and setting it in the the program‎.

 &nb

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Publication Date
Sun Mar 06 2016
Journal Name
Baghdad Science Journal
A Note on the Perturbation of arithmetic expressions
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In this paper we present the theoretical foundation of forward error analysis of numerical algorithms under;• Approximations in "built-in" functions.• Rounding errors in arithmetic floating-point operations.• Perturbations of data.The error analysis is based on linearization method. The fundamental tools of the forward error analysis are system of linear absolute and relative a prior and a posteriori error equations and associated condition numbers constituting optimal of possible cumulative round – off errors. The condition numbers enable simple general, quantitative bounds definitions of numerical stability. The theoretical results have been applied a Gaussian elimination, and have proved to be very effective means of both a prior

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Publication Date
Thu Feb 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
SUGGESTING MULTIPHASE REGRESSION MODEL ESTIMATION WITH SOME THRESHOLD POINT
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The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t

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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
Dynamic Fault Tolerance Aware Scheduling for Healthcare System on Fog Computing
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 Internet of Things (IoT) contributes to improve the quality of life as it supports many applications, especially healthcare systems. Data generated from IoT devices is sent to the Cloud Computing (CC) for processing and storage, despite the latency caused by the distance. Because of the revolution in IoT devices, data sent to CC has been increasing. As a result, another problem added to the latency was increasing congestion on the cloud network. Fog Computing (FC) was used to solve these problems because of its proximity to IoT devices, while filtering data is sent to the CC. FC is a middle layer located between IoT devices and the CC layer. Due to the massive data generated by IoT devices on FC, Dynamic Weighted Round Robin (DWRR)

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
A Proposed Algorithm for Encrypted Data Hiding in Video Stream Based on Frame Random Distribution
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     The science of information security has become a concern of many researchers, whose efforts are trying to come up with solutions and technologies that ensure the transfer of information in a more secure manner through the network, especially the Internet, without any penetration of that information, given the risk of digital data being sent between the two parties through an insecure channel. This paper includes two data protection techniques. The first technique is cryptography by using Menezes Vanstone elliptic curve ciphering system, which depends on public key technologies. Then, the encoded data is randomly included in the frame, depending on the seed used. The experimental results, using a PSNR within avera

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
A Novel Technique for Secure Data Cryptosystem Based on Chaotic Key Image Generation
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The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Checking the Accuracy of Selected Formulae for both Clear Water and Live Bed Bridge Scour
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Due to severe scouring, many bridges failed worldwide. Therefore, the safety of the existing bridge (after contrition) mainly depends on the continuous monitoring of local scour at the substructure. However, the bridge's safety before construction mainly depends on the consideration of local scour estimation at the bridge substructure. Estimating the local scour at the bridge piers is usually done using the available formulae. Almost all the formulae used in estimating local scour at the bridge piers were derived from laboratory data. It is essential to test the performance of proposed local scour formulae using field data. In this study, the performance of selected bridge scours estimation formulae was validated and sta

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
An Analysis on the Applicability of Meta-Heuristic Searching Techniques for Automated Test Data Generation in Automatic Programming Assessment
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Automatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient t

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Publication Date
Sun Jul 30 2023
Journal Name
Iraqi Journal Of Science
Exact and Near Pareto Optimal Solutions for Total Completion Time and Total Late Work Problem
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     In this paper, the bi-criteria machine scheduling problems (BMSP) are solved, where the discussed problem is represented by the sum of completion and the sum of late work times  simultaneously. In order to solve the suggested BMSP, some metaheurisitc methods are suggested which produce good results. The suggested local search methods are simulated annulling and bees algorithm. The results of the new metaheurisitc methods are compared with the complete enumeration method, which is considered an exact method, then compared results of the heuristics with each other to obtain the most efficient method.

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