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Comparing Bayesian methods to estimate the failure probability for electronic systems in case the life time data are not available
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In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the technical staff of the company and by using the range as statistical criterion.

 

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of Voluntary Obedience for Tthe Taxpayers to Find End to Tax Evasions in Iraq
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The Voluntary Obedience has great importance for the modern taxes systems and its management and this is meant the taxpayer whom in charge to pay of his taxes obligations voluntarily , he is very known of himself whereas he prepared his finishing accountings and present them as samples prepared by taxes management and settle the tax sum directly according to specified income , which has an impact to find end to tax evasion as result lead to increase the tax income and achieve the justice for the taxpayer and the state treasury

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)
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In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

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Publication Date
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
The distance variation due to mass transfer and mass loss in (13.6+8) Mand (13+10) M binary star systems
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In this research the change in the distance of the two stars in two binary star systems (13.6+8)M8and (13+10)Mwas studied, through the calculations the value  (rate of mass transfer) of the two phases of dynamical stages of mass which are mass loss and mass transfer has been extracted in its own way ,by extracting the value of  the value of (the distance variation between the two stars) has been found only in the mass transfer stage by using mathematical model ,in mass loss stage  and   were calculated from the change and the difference between the values of each at different times of binary star system evolution ,it was found that  the maximum values of  and  are in ma

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Publication Date
Wed Oct 18 2023
Journal Name
Ieee Access
A New Imputation Technique Based a Multi-Spike Neural Network to Handle Missing Data in the Internet of Things Network (IoT)
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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
THE ROLE OF SOCIAL ENTREPRENEURSHIP IN IMPROVING THE QUALITY OF LIFE OF THE CUSTOMER Field research at the Iraqi Ministry of Labor and Social Affairs
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Abstract:
      This research emerged due to the needs of Iraqi social sector for diagnosing the problems ,finding the appropriate solutions,and exploiting the social opportunities to solve these problems .The research problem focused on raising the following question: "Were Iraqi Managers in the Ministry of Labor and Social Affairs able to use their qualifications as social entrepreneurs in the ministry to improve the quality of life of the disadvantaged groups?", In light of that, the importance and objectives of the study were determined, and this research derives its importance from trying to address social problems by measuring the degree of meeting the subjective and objective needs of the custo

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Global Pharma Technology
Some Biochemical Parameters in Congestive Heart Failure Patients in Baghdad City
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Publication Date
Thu Jul 23 2026
Journal Name
Journal Of Babylon Center For Humanities Studies
The manifestations of existentialism in the novel &quot;Life as an example&quot; by writer Pinchas Sadia
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Publication Date
Mon Sep 01 2014
Journal Name
Proceedings Of Ieee East-west Design &amp; Test Symposium (ewdts 2014)
Qubit method for diagnosing digital systems
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Publication Date
Mon Apr 01 2019
Journal Name
2019 International Conference On Automation, Computational And Technology Management (icactm)
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
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Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

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Publication Date
Thu Dec 01 2011
Journal Name
Iraqi Journal Of Physics
Multilayer Perceptron for analyzing satellite data
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Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

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