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Evolutionary Based Set Covers Algorithm with Local Refinement for Power Aware Wireless Sensor Networks Design
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Establishing coverage of the target sensing field and extending the network’s lifetime, together known as Coverage-lifetime is the key issue in wireless sensor networks (WSNs). Recent studies realize the important role of nature-inspired algorithms in handling coverage-lifetime problem with different optimization aspects. One of the main formulations is to define coverage-lifetime problem as a disjoint set covers problem. In this paper, we propose an evolutionary algorithm for solving coverage-lifetime problem as a disjoint set covers function. The main interest in this paper is to reflect both models of sensing: Boolean and probabilistic. Moreover, a heuristic operator is proposed as a local refinement operator to improve the quality of the solutions provided by the evolutionary algorithm. Simulation results show the necessity to inject a heuristic operator within the mechanism of evolutionary algorithm to improve its performance. Additionally, the results show performance difference while adopting the two types of sensing models.

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Heart Disease Classification–Based on the Best Machine Learning Model
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    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

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Publication Date
Fri Jul 01 2011
Journal Name
Engineering And Technology Journal
Off-Line Arabic Signature Recognition Based on Invariant Moments Properties
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Publication Date
Thu Nov 25 2021
Journal Name
Engineering And Technology Journal
Pentacene Based Organic Field Effect Transistor Using Different Gate Dielectric
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This paper presents the electrical behavior of the top contact/ bottom gate of an organic field-effect transistor (OFET) utilizing Pentacene as a semiconductor layer with two distinctive gate dielectric materials Polyvinylpyrrolidone (PVP) and Zirconium oxide (ZrO2) were chosen. The influence of the monolayer and bilayer gates insulator on OFET performance was investigated. MATLAB software was used to simulate and determine the electrical characteristics of a device. The output and transfer characteristics were studied for ZrO2, PVP and ZrO2/PVP as an organic gate insulator layer. Both characteristics show a high drain current at the gate dielectric ZrO2/PVP equal to -0.0031A and -0.0015A for output and transfer characteristics respectively

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Publication Date
Sat Mar 29 2014
Journal Name
International Journal Of Academic Research In Progressive Education And Development
The Effects of Problem-Based Learning on Self-Directed Learning Skills among Physics Undergraduates
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The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette

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Publication Date
Mon Jan 03 2022
Journal Name
Iraqi Journal Of Science
Accuracy Assessment of 3D Model Based on Laser Scan and Photogrammetry Data: Introduction
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    A three-dimensional (3D) model extraction represents the best way to reflect the reality in all details. This explains the trends and tendency of many scientific disciplines towards making measurements, calculations and monitoring in various fields using such model. Although there are many ways to produce the 3D model like as images, integration techniques, and laser scanning, however, the quality of their products is not the same in terms of accuracy and detail. This article aims to assess the 3D point clouds model accuracy results from close range images and laser scan data based on Agi soft photoscan and cloud compare software to determine the compatibility of both datasets for several applications. College of Scien

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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
Effect Of Vêo® Premium and Vitamin C Supplementation on Lipid Profile Before and During Pregnancy in Some Local Iraqi Ewes During Heat Stress
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The present study was designed to investigate the effects of VêO® premium and vitamin C (Vit. C) supplementation on lipid profile before and during pregnancy in local Iraqi ewes during heat stress. The study was conducted in a private field in Fallujah city, west Iraq, during the period from 6/8/2019 to 8/2/2020. Twenty local Iraqi ewes were divided randomly into four equal groups (5 for each group) The first group (T1) was given VêO® premium (4 g/ ewe/ day), the second group (T2) was given VêO® premium (2 g/ ewe/ day), and the third group (T3) was given Vit. C (40 mg/ ewe/ day), and the fourth group (T4) was left without treatment, as a control group. Aft

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Publication Date
Thu Jun 02 2022
Journal Name
Neuroquantology
The effect of the relationship of leptin hormone and live body weight on some chemical characteristics of the blood serum of local laying hens
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The study was conducted out at the Ministry of Agriculture's Poultry Research Station/Animal ResourcesDepartment/Agricultural Research Center. To see how body weight (BW) and leptin hormone (LEP) levels inbreeder blood affect fertility and hatchability. 140 Iraqi local laying chickens (120 females + 20 males) aged 28weeks were used in the study. Following the numbering of The experiment was divided into three periods,each lasting 28 days, during which the breeder's live body weight was recorded and divided into two categories(greater than 1.5 kg and less than 1.5 kg), and blood samples were collected at the end of each period todetermine the concentration of leptin hormone in the breeders' blood. For comparison between mothers'performance,

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Publication Date
Mon May 15 2023
Journal Name
Iraqi Journal Of Science
Using Linear Local Dependence Measure to Study the factors that are Leading to the Growth of Preferring the Application in Private Universities of Iraq
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In this paper a measure of linear local dependence has been used between two
random variables and a study is conducted for the properties of this measure where
two examples of bivariate probability distributions has been considered, which are
bivariate Gumbel distribution and bivariate Beta-Stacy distribution, and applied on
data collected by using a questionnaire conducted to study the reasons for the
increase of application in private collages in Iraq. Five elements has been considered
as random variables and the dependence has been measured between every two
elements to estimate how correlated these elements are and their effect on the
application in private collages of Iraq generally and Baghdad specifically.<

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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
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Improved throughput of Elliptic Curve Digital Signature Algorithm (ECDSA) processor implementation over Koblitz curve k-163 on Field Programmable Gate Array (FPGA)
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            The widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most suitable choice for the environments due to the smaller size of the encryption key and changeable security related parameters. However, major performance metrics such as area, power, latency and throughput are still customisable and based on the design requirements of the device.

The present paper puts forward an enhancement for the throughput performance metric by p

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