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A Parallel Clustering Analysis Based on Hadoop Multi-Node and Apache Mahout

     The conventional procedures of clustering algorithms are incapable of overcoming the difficulty of managing and analyzing the rapid growth of generated data from different sources. Using the concept of parallel clustering is one of the robust solutions to this problem. Apache Hadoop architecture is one of the assortment ecosystems that provide the capability to store and process the data in a distributed and parallel fashion. In this paper, a parallel model is designed to process the k-means clustering algorithm in the Apache Hadoop ecosystem by connecting three nodes, one is for server (name) nodes and the other two are for clients (data) nodes. The aim is to speed up the time of managing the massive scale of healthcare insurance dataset with the size of 11 GB and also using machine learning algorithms, which are provided by the Mahout Framework. The experimental results depict that the proposed model can efficiently process large datasets. The parallel k-means algorithm outperforms the sequential k-means algorithm based on the execution time of the algorithm, where the required time to execute a data size of 11 GB is around 1.847 hours using the parallel k-means algorithm, while it equals 68.567 hours using the sequential k-means algorithm. As a result, we deduce that when the nodes number in the parallel system increases, the computation time of the proposed algorithm decreases.

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Publication Date
Fri Nov 20 2020
Journal Name
Solid State Technology
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Publication Date
Mon Oct 11 2021
Journal Name
Nano Hybrids And Composites
Far Infrared Laser Detector Based on Multi-Walled Carbon Nanotubes and Blend of (Polyaniline - Polymethyl Methacrylate) Polymers with Methyl Blue Dye for Photoconductive Applications

Infrared photoconductive detectors working in the far-infrared region and room temperature were fabricated. The detectors were fabricated using three types of carbon nanotubes (CNTs); MWCNTs, COOH-MWCNTs, and short-MWCNTs. The carbon nontubes suspension is deposited by dip coating and drop–casting techniques to prepare thin films of CNTs. These films were deposited on porous silicon (PSi) substrates of n-type Si. The I-V characteristics and the figures of merit of the fabricated detectors were measured at a forward bias voltage of 3 and 5 volts as well as at dark and under illumination by IR radiation from a CO2 laser of 10.6 μm wavelengths and power of 2.2 W. The responsivity and figures of merit of the photoconductive detector

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
A Lightweight Image Encryption Algorithm Based on Elliptic Curves and a 5D Logistic Map

    Cryptography can be thought of as a toolbox, where potential attackers gain access to various computing resources and technologies to try to compute key values. In modern cryptography, the strength of the encryption algorithm is only determined by the size of the key. Therefore, our goal is to create a strong key value that has a minimum bit length that will be useful in light encryption. Using elliptic curve cryptography (ECC) with Rubik's cube and image density, the image colors are combined and distorted, and by using the Chaotic Logistics Map and Image Density with a secret key, the Rubik's cubes for the image are encrypted, obtaining a secure image against attacks. ECC itself is a powerful algorithm that generates a pair of p

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Publication Date
Tue Jun 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
A new pseudorandom bits generator based on a 2D-chaotic system and diffusion property

A remarkable correlation between chaotic systems and cryptography has been established with sensitivity to initial states, unpredictability, and complex behaviors. In one development, stages of a chaotic stream cipher are applied to a discrete chaotic dynamic system for the generation of pseudorandom bits. Some of these generators are based on 1D chaotic map and others on 2D ones. In the current study, a pseudorandom bit generator (PRBG) based on a new 2D chaotic logistic map is proposed that runs side-by-side and commences from random independent initial states. The structure of the proposed model consists of the three components of a mouse input device, the proposed 2D chaotic system, and an initial permutation (IP) table. Statist

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Proposed Security Models for Node-level and Network-level Aspects of Wireless Sensor Networks Using Machine Learning Techniques

     As a result of the pandemic crisis and the shift to digitization, cyber-attacks are at an all-time high in the modern day despite good technological advancement. The use of wireless sensor networks (WSNs) is an indicator of technical advancement in most industries. For the safe transfer of data, security objectives such as confidentiality, integrity, and availability must be maintained. The security features of WSN are split into node level and network level. For the node level, a proactive strategy using deep learning /machine learning techniques is suggested. The primary benefit of this proactive approach is that it foresees the cyber-attack before it is launched, allowing for damage mitigation. A cryptography algorithm is put

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
Hartha Formation divisions Based on Well Logs Analysis in Majnoon Oil Field, Southern Iraq

This study aims to evaluate reservoir characteristics of Hartha Formation in Majnoon oil field based on well logs data for three wells (Mj-1, Mj-3 and Mj-11). Log interpretation was carried out by using a full set of logs to calculate main petrophysical properties such as effective porosity and water saturation, as well as to find the volume of shale. The evaluation of the formation included computer processes interpretation (CPI) using Interactive Petrophysics (IP) software.  Based on the results of CPI, Hartha Formation is divided into five reservoir units (A1, A2, A3, B1, B2), deposited in a ramp setting. Facies associations is added to well logs interpretation of Hartha Formation, and was inferred by a microfacies analysis of th

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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Potentiometric Analysis of Samarium Ion in Aqueous Solution Employing Selective Electrode Based on Crown Ethers - Samarium Picrate Complexes in a PVC Membrane

Samarium  ion selective  electrodes  we1·e  construct.ed  and  prepared

then  tested as  probefor  Samarium  ion detection  and determination  in different aqueous solutions.

The sensitive membrane is made of  PVC which contains Samarium

picrate complexed with either 18-crown-6 or 15-crown-5 ethers as active species.

Different  plasticizers:  phthalates  (DBPH),  phosphates  (DBP)  and

phosphonates  (DOPP) were incorporated into the membranes as solvent

mediators.

Every   membrane   was   evaluated   practically   following  &n

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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
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