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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
Sat Apr 01 2017
Journal Name
25th Gis Research Uk Conference
VGI data collection for supplementing official land administration systems
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This article explores the process of VGI collection by assessing the relative usability and accuracy of a range of different methods (Smartphone GPS, Tablet, and analogue maps) for data collection amongst different demographic and educational groups, and in different geographical contexts. Assessments are made of positional accuracy, completeness, and data collectors’ experiences with reference to the official cadastral data and the administration system in a case-study region of Iraq. Ownership data was validated by crowd agreement. The result shows that successful VGI projects have access to varying data collection methods.

Publication Date
Tue Jan 01 2008
Journal Name
2008 15th Asia-pacific Software Engineering Conference
G2Way A Backtracking Strategy for Pairwise Test Data Generation
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Publication Date
Sun Jan 01 2017
Journal Name
Proceedings Of The Conference “recent Trends In Engineering Sciences And Sustainability”, Baghdad
GNSS positioning techniques for enhancing Google Earth data quality
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Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Compression-based Data Reduction Technique for IoT Sensor Networks
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Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

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Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Formation Evaluation for Nasiriyah Oil Field Based on The Non-Conventional Techniques
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The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence. The techniques used in this paper are:

  • Apparent resistivity Rwa
  • Rxo /Rt

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Anaerobic Digestion and Codigestion of Chlorella Vulgaris Microalgae Biomass with Wastewater Sludge and Dairy Manure for Biogas Production
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Abstract

 

Anaerobic digestion process of organic materials is biochemical decomposition process done by two types of digestion bacteria in the absence of oxygen resulting in the biogas production, which is produced as a waste product of digestion. The first type of bacteria is known as acidogenic which converts organic waste to fatty acids. The second type of bacteria is called methane creators or methanogenic which transforms the fatty acids to biogas (CH4 and CO2). The considerable amounts of biodegradable constitutes such as carbohydrates, lipids and proteins present in the microalgae biomass make it a suitable substrate for the anaerobic digestion or even c

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Estimator for the Scale Parameter of the Normal Distribution Under Different Prior Distributions
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In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering
Design And Analysis Performance of Liquid Petroleum Gases System in Residential Building; Review
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Liquefied petroleum gases (LPG) consist of hydrocarbons obtained by refining crude oil, either from propane or butane or a mixture of the two. There are often other components such as propylene, butylene or other hydrocarbons, but they are not the main component. The study aims to review previous studies dealing with designing an LPG system to deliver gas to residential campuses and buildings. LPG is extracted from natural gas NG by several processes, passing through fractionation towers and then pressuring into CNG storage tanks. Gas contains several problems, including gas leakage through the pipes and leads to fires or explosions in LPG storage and distribution tanks, so safety conditions were taken in the design and implementation. T

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Compound Heat Transfer Enhancement in Dimpled and Sinusoidal Metal Solar Wall Ducts Fitted with Wired Inserts
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An improved Metal Solar Wall (MSW) with integrated thermal energy storage is presented in this research. The proposed MSW makes use of two, combined, enhanced heat transfer methods. One of the methods is characterized by filling the tested ducts with a commercially available copper Wired Inserts (WI), while the other one uses dimpled or sinusoidal shaped duct walls instead of plane walls. Ducts having square or semi-circular cross sectional areas are tested in this work.
A developed numerical model for simulating the transported thermal energy in MSW is solved by finite difference method. The model is described by system of three governing energy equations. An experimental test rig has been built and six new duct configurations have b

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Effect of Orgnizational Learning in gnizational Effectifness: An Applied Study
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The purpose of this study is testing the effect of orgnizational learning in orgnizational Effectivness an applied study in Al-hiqma Jordinan Medecine Company . study sosiety 88 manegers sleect 80 of them .study used SPSS to test the hypothesis.study reachs to significant conculctions

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