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bsj-2428
Revaluation of Student Failure Reasons Using Non-Additive Methods
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In this paper, An application of non-additive measures for re-evaluating the degree of importance of some student failure reasons has been discussed. We apply non-additive fuzzy integral model (Sugeno, Shilkret and Choquet) integrals for some expected factors which effect student examination performance for different students' cases.

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Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
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This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
comparison between the methods estimate nonparametric and semiparametric transfer function model in time series the Using simulation
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 The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method  local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Wed Jul 01 2015
Journal Name
Al–bahith Al–a'alami
Methods of Arab TV Programs Production
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This research investigates the methods of producing Investigative Arabic Television Programs that are able to prove its existence during a short period of time as a form of Television programs on Arab satellite channels growing in number and varied in content. The research aims to present qualitative and quantitative descriptions of the methods used in tackling the topics discussed in the program, and knowing whether they satisfy the conditions and scientific foundations for the research, investigation, analysis, and interpretation. The researcher uses the survey method and uses the tool of content analysis including a set of methodological steps that seek to discover the implied meaning of the research sample represented by the program

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Hurst exponent estimation methods
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Through recent years many researchers have developed methods to estimate the self-similarity and long memory parameter that is best known as the Hurst parameter. In this paper, we set a comparison between nine different methods. Most of them use the deviations slope to find an estimate for the Hurst parameter like Rescaled range (R/S), Aggregate Variance (AV), and Absolute moments (AM), and some depend on filtration technique like Discrete Variations (DV), Variance versus level using wavelets (VVL) and Second-order discrete derivative using wavelets (SODDW) were the comparison set by a simulation study to find the most efficient method through MASE. The results of simulation experiments were shown that the performance of the meth

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Publication Date
Sat Jul 01 2017
Journal Name
Global Journal Of Bio-science And Biotechnology
Efficiency of different denture disinfection methods
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Dentures that are not cleaning and maintained properly may prone to contamination by different microbial pathogens that result in several oral conditions. This study was design to compare the antimicrobial effect of different denture cleansers oxalic, tartaric, citric acids and alkaline peroxide with microwave irradiation on the growth of Candida albicans and Staphylococcus aureus respectively. Microwave oven used to disinfect specimens of heat-activated acrylic resin and soft linear. Oxalic, citric, tartaric acids, and alkaline peroxide were also used. Microorganisms that tested were Candida albicans and Staphylococcus aureus separately. Treatment with microwave or tartaric acid could achieve sterilization of both hot cured acrylic resins

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Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
Simplification of new fashion design methods
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Simplification of new fashion design methods

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Hurst exponent estimation methods
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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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