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Unsupervised Segmentation Method for Thyroid Nodules in Ultrasound Images
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Thyroid is a small butterfly shaped gland located in the front of the neck just below the Adams apple. Thyroid is one of the endocrine gland, which produces hormones that help the body to control metabolism. A different thyroid disorder includes Hyperthyroidism, Hypothyroidism, and thyroid nodules (benign/malignant). Ultrasound imaging is most commonly used to detect and classify abnormalities of the thyroid gland. Segmentation method is a tool that used widely in many applications including medical image processing. One of the common applications of segmentation is in medical image analysis for clinical diagnosis that has an important role in terms of quality and quantity.
The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of thyroid tumors. Thyroid ultrasound images may contain speckle noise which leads to obtain incorrect result. In order to obtain good accuracy; the noise must be removed from the input image. Those propose method is started with pre-processing of the thyroid ultrasound image to enhance its contrast and removing the undesired noise in order to make the image suitable for further processing. In our proposed work, we are using bilateral filter and unsharp filter to remove speckle noise to perform the pre-processing operations on the thyroid ultrasound images. The segmentation process is performed by using Fuzzy C-Means (FCM) algorithm to detect and segment thyroid ultrasound images for the thyroid region extracted image to 6 classes for two sample normal and abnormal images. The resulted segmented ultrasound images, and then used to extract the tumor region from thyroid's image.

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Publication Date
Thu Feb 15 2024
Journal Name
Al-manhaj Library
Multivariate Analysis - Second Edition
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This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr

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Publication Date
Thu Feb 15 2024
Journal Name
Al-manhaj Library
Multivariate Analysis (Second Edition)
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This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr

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Publication Date
Tue Apr 24 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Securing digital documents using digital watermarking
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     The intellectual property of digital documents has been protected by using many methods of digital watermarking. Digital documents have been so much of advantages over print documents. Digital documents are less expensive and easy to store, transport, and searched compared to traditional print documents.  But it has its owner limitation too. A simple image editor can be used to modify and make a forged document. Digital documents can be tampered easily. In order to utilize the whole benefits of digital document, these limitations have to overcome these limitations by embedding some text, logo sequence that identifies the owner of the document..

In this research LSB  technique  has been used

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Discussing Fuzzy Reliability Estimators of Function of Mixed Probability Distribution By Simulation
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This paper deals  with constructing mixed probability distribution  from exponential with scale parameter (β) and also Gamma distribution with (2,β), and the mixed proportions are (  .first of all, the probability density function (p.d.f) and also cumulative distribution function (c.d.f) and also the reliability function are obtained. The parameters of mixed distribution, ( ,β)  are estimated by three different methods, which are  maximum likelihood, and  Moments method,as well proposed method (Differential Least Square Method)(DLSM).The comparison is done using simulation procedure, and all the results are explained in tables.

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Publication Date
Sat Dec 01 2012
Journal Name
Iraqi Journal Of Physics
Elastic electron scattering from some 2s-1d shell nuclei
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The charge density distributions (CDD) and the elastic electron
scattering form factors F(q) of the ground state for some even mass
nuclei in the 2s 1d shell ( Ne Mg Si 20 24 28 , , and S 32 ) nuclei have
been calculated based on the use of occupation numbers of the states
and the single particle wave functions of the harmonic oscillator
potential with size parameters chosen to reproduce the observed root
mean square charge radii for all considered nuclei. It is found that
introducing additional parameters, namely 1 , and , 2  which
reflect the difference of the occupation numbers of the states from
the prediction of the simple shell model leads to a remarkable
agreement between the calculated an

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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 Oct 28 2020
Journal Name
Iraqi Journal Of Science
Electron Scattering from Some Fp- Shell Nuclei with Inclusion the Effect of Short-Range Correlation
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The effects of short-range correlation on elastic Coulomb (charge) form factors, charge density distributions as well as root mean square charge radii of various  nuclei (for instance, 46, 48, 50Ti, 52, 54Cr, 56, 58Fe, and 72, 74, 76Ge nuclei) are examined. The one- and two body terms of the cluster expansion together with the single-particle harmonic oscillator wave functions are utilized. For the purpose of embedding these effects into the formulae of charge density  and form factor  we employ the correlation function of Jastrow-type. These formulae depend upon the short-range correlation parameter  (which instigates from the Jastr

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Publication Date
Wed Dec 22 2021
Journal Name
Plos One
Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries
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Background

Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave.

Methods

This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Study of Matter Density Distributions, Elastic Electron Scattering Form factors and Root Mean Square Radii of 9C, 12N, 23Al, 11Be and 15C Exotic Nuclei
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    The ground state densities of neutron-rich (11Be,15C) and proton-rich (9C,12N,23Al) exotic nuclei are investigated using a two-body nucleon density distribution (2BNDD) with two frequency shells model (TFSM). The structure of the valence one-neutron of 11Be is in pure (1p1/2) and of 15C in pure (1d5/2) configuration, while the structure of valence one-proton configuration is in 9C,12N are to be in a pure (1p1/2) and 23Al in a pure  (2s1/2) . For our studied nuclei, an efficient (2BNDD) operator for point nucleon system folded with two-body correlation operator's functions is  u

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Publication Date
Sun Jul 02 2023
Journal Name
Iraqi Journal Of Science
Study of Density Distributions, Elastic Electron Scattering form factors and reaction cross sections of 9C, 12N and 23Al exotic nuclei
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The ground state densities of unstable proton-rich 9C, 12N and 23Al exotic nuclei are studied via the framework of the two-frequency shell model (TFSM) and the binary cluster model (BCM). In TFSM, the single particle harmonic oscillator wave functions are used with two different oscillator size parameters βc and βv, where the former is for the core (inner) orbits and the latter is for the valence (halo) orbits. In BCM, the internal densities of the clusters are described by single particle Gaussian wave functions. The long tail performance is clearly noticed in the calculated proton and matter density distributions of these nuclei. The structure of the valence proton in 9C and 12N is a pure (1p1/2) configuration while that for 23Al is

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