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jeasiq-751
Building discriminant function for repeated measurements data under compound symmetry (CS) covariance structure and applied in the health field
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Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

 

The importance of this research represented to find the best model  to classify  a  group of  patients who  suffer  from diabetes.  For  the purpose of studying the effects of  the number of correlations, variances, and umber of  repeated  measurements  on the performance of classification rules for this  type of  data  based on monthly measurements  of  glycosylated  hemoglobin (HbA1C) in the blood was taken in three stages, which  is  the beginning  of  the experiment, and after three months, and  then  six  months for two groups of patients, the first group consists of  (38)  patients  was  suffered  from  diabetes  type (I)  and  the second group includes (33) patients suffered from diabetes type (II).

 

And through this research, concluded that when the number of parameters began to increase. Thus, the apparent error rate  begin to increasing, and this is what reduces the efficiency of classification rules for this type of data. And  we  recommend  by  using  the linear discriminant function when you focus on the least number of parameters to build the classification rule. And quadratic discriminant procedure Represented by equal the variance and different correlation parameters  under compound symmetry covariance structures

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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
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Tue Mar 05 2019
Journal Name
Biomedical And Pharmacology Journal
Prevalence and Public Health Importance of Hydatidosis in Sheep Slaughtered by Unlicensed Ways
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Hydatidosis is a zoonotic, helminthes parasitic disease that cause veterinary and human problems due to economic burden. Amis of the current study was to estimate the prevalence rate of hydatidosis infecting different organs of sheep slaughtered in street. In addition, investigate the relationship between age, gender and the infected rates in some Baghdad areas during a period from may to end of July 2018.A total of 188 sheep was examined for detection of Hydatid cyst in different organs using macroscopic and microscopic examination The overall prevalence rate of 47.9% was recorded. The results indicate non significant differences according to age and gender, the highest rate 57% was observed in sheep more than one year old compare

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Publication Date
Mon Mar 28 2022
Journal Name
Nurse Media Journal Of Nursing
Health Literacy-Related Knowledge and Experience among Nurses Practicing in Medical-Surgical Wards
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Background: Medical-surgical nurses are responsible of providing competent care to clients with a wide-array of acute and chronic health problems. This challenging task requires arming nurses with advanced competencies of health literacy to effectively educate their clients. However, evidence about medical-surgical nurse’s health literacy-related knowledge and experience is limited.  Purposes: This study aimed to determine the level of the health literacy-related knowledge and experience among medical-surgical nurses.Design: A descriptive-cross-sectional study was conducted among a total sample of 177 nurses who were practicing in medical-surgical wards in teaching hospitals in Iraq. A convenience sampling method was used to sele

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Publication Date
Wed Apr 06 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role Talents Management in Consolidating Organizational Learning Process: An Applied Study at the Yemeni General Telecommunications Corporation
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This study aimed at accounting for the role of talents management in consolidating organizational learning process at the Yemeni General Corporation For telecommunication. To achieve the objective of the study, the researcher designed a questionnaire and administered it. The sample of the study consisted of (166) employees (General Manager, Manager and Department Head). They were selected randomly out of a total Population of (291) employees during the Year 2019. The descriptive analytic approach was used t reach conclusions.

The finding of the study revealed existence of effect of talents management dimensions, all together and alone, (talents polarization, talents development, talents maintenance and ma

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
First Transition Metal Complexes Salts of Diazonium Derived from Nitrogen Heterocyclic Compound, Synthesis, Characterization and Biological Activity
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Metal complexes chrome(III), manganese(II), iron(III), cobalt(II), nickel(II), cupper(II) and zinc(II) with diazonium of 3-amino-2-chloropyridine of general formula [2-Cl-C5H3N≡N]n[MXm], where n=2 or 3 for divalent and trivalent metal, m= 4 or 6  were synthesized. The complexes have been characterized by flame atomic absorption, (C.H.N), molar conductance, magnetic susceptibility UV-vis spectra, infrared spectra,1H-NMR spectroscopy and thermo gravimetric analysis (TGA and DTA). The measurements showed that the divalent metal ion complexes (M2+) have (1:2) M:L ratio with tetrahedral geometry around metal ions while the trivalent metal ions (M3+) formed (1:3) m

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Publication Date
Sun May 10 2020
Journal Name
Baghdad Science Journal
Characterization and Biological Activity of Some New Derivatives Derived from Sulfamethoxazole Compound: new derivatives from sulfamethoxazole drug.
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 A new series of Sulfamethoxazole derivatives was prepared and examined for antifibrinolytic and antimicrobial activities. Sulfamethoxazole derivatives bear heterocyclic moieties such as 1,3,4-thiadiazine {3},  pyrazolidine-3,5-diol {4} 6-hydroxy-1,3,4-thiadiazinane-2-thione {5} and [(3-methyl-5-oxo-4,5-dihydro-1H-pyrazol-4-yl)diazenyl] {8}. Their structures were elucidated by spectral methods (FT-IR, H1-NMR). Physical properties are also determined for all compound derivatives.  Recently prepared compounds were tested for their antimicrobial activity in the laboratory. Each screened compound showed good tendency to moderate antimicrobial activity.

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