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Estimation Of Left Ventricular Ejection Fraction Using Mitral Annular Displacement Derived By Speckle Tracking Echocardiography In Patients With Different Heart Diseases
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Background: Speckle tracking echocardiography (STE)-derived mitral annular displacement (MAD) utilizes the speckle tracking technique to measure strain vectors, which provides accurate estimates of left ventricular ejection fraction (LVEF).Objectives: To validate the accuracy of mitral annular displacement (MAD), assessed by Speckle Tracking Echocardiography (STE), as a surrogate for determination of left ventricular systolic function in comparison to 2-Dimensions Simpson method in patients with different heart diseases.Methods : This cross-sectional study included patients who referred to outpatient department of Ibn Albitar Center for Cardiac Surgery, Baghdad, Iraq, between October 2012 and April 2013. STE continuously tracked annular motion throughout the cardiac cycle in the apical 4- and 2-chamber views. LVEF for each patient was measured by both Simpson method and STE-derived MAD.Results: This study included 100 patients, of them (35%) had ischemic heart disease (IHD), (10%) had dilated cardiomyopathy (DCM), (10%) had valvular heart disease (VHD), (25%) had normal echocardiography, and (20%) had hypertensive heart disease (HHD).There was significant correlation between EF % (derived by MAD) and EF % (derived by Simpson method) in patients with different heart diseases. This correlation was good in normal subjects (r=0.673), and those with IHD(r=0.896), DCM (r=0.724) and VHD (r=0.935), while in HHD it was moderately correlated (r=0.455). There was slight under-estimation of LVEF derived by MAD (a mean value of difference 0.846 %; p =0.022). In subgroup analysis, this difference was seen only in patients with HHD (a mean value of difference 3.145 %; p <0.001), while it was absent in other subgroups.Conclusion: STE-derived MAD provides easy, fast, and accurate assessments of global longitudinal systolic function. LVEF derived by MAD was correlated well with LVEF derived by Simpson method in patients with different heart diseases

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Publication Date
Mon May 16 2016
Journal Name
Far East Journal Of Mathematical Sciences (fjms)
MINIMIZING WAITING TIMES USING MULTIPLE FUZZY QUEUEING MODEL WITH SUPPLY PRIORITIES
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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Predicting changes on budget expenditures using Markov chains with practical application
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The researchers have a special interest in studying  Markov  chains as one of the probability samples which has many applications in different fields. This study comes to deal with the changes issue that happen on budget expenditures by using statistical methods, and Markov chains is the best expression about that as they are regarded reliable  samples in the prediction process. A transitional matrix is built for three expenditure cases (increase ,decrease ,stability) for one of budget expenditure items (base salary) for three directorates (Baghdad ,Nineveh , Diyala) of one  of the ministries. Results are analyzed by applying  Maximum likelihood estimation  and Ordinary least squares  methods resulting

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Parametric Nonlinear Programming Approach with Fuzzy Queues Using Hexagonal Membership Functions
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Publication Date
Tue Jun 01 2021
Journal Name
Periodicals Of Engineering And Natural Sciences
Steganography using dual tree complex wavelet transform with LSB indicator technique
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Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p

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Publication Date
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
Nuclear level density with proton resonance using Gaussian orthogonal ensemble theory
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The Gaussian orthogonal ensemble (GOE) version of the random matrix theory (RMT) has been used to study the level density following up the proton interaction with 44Ca, 48Ti and 56Fe.

A promising analysis method has been implemented based on the available data of the resonance spacing, where widths are associated with Porter Thomas distribution. The calculated level density for the compound nuclei 45Sc,49Vand 57Co shows a parity and spin dependence, where for Sc a discrepancy in level density distinguished from this analysis probably due to the spin  misassignment .The present results show an acceptable agreement with the combinatorial method of level density.

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
A multivariate Bayesian model using Gibbs sampler with real data application
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In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
The efficiency of cluster analysis to analyzing medical image of Covid-19 patient by using K-means algorithm
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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Learning for Scientific Culture by Using Interactive Whiteboard According to the Faculty of the University of Baghdad Viewpoint
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The progress of science in all its branches and levels made great civilized changes of
our societies in the present day, it's a result of the huge amount of knowledge, the increase of
number of students, and the increase of community awareness proportion of the importance of
education in schools and universities, it became necessary for us as educators to look at
science from another point of view based on the idea of scientific development of curricula
and teaching methods and means of education, and for the studying class environment as a
whole, by computer and internet use in education to the emergence of the term education
technology, which relies on the use of modern technology to provide educational content to<

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
The Effective of Pressure and Sintering Temperature for Hardness Characteristics of Shape Memory Alloy by Using Taguchi Technique
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This paper presents the Taguchi approach for optimization of hardness for  shape memory alloy (Cu-Al-Ni) . The influence of  powder metallurgy parameters on hardness has been investigated. Taguchi technique and ANOVA were used for analysis. Nine experimental runs based on Taguchi’s L9 orthogonal array were performed (OA),for two parameters was study (Pressure and sintering temperature) for three different levels (300 ,500 and 700) MPa ,(700 ,800 and  900)oC respectively . Main effect, signal-to-noise (S/N) ratio was study, and analysis of variance (ANOVA) using  to investigate the micro-hardness characteristics of the shape memory alloy .after application the result of study shown the hei

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