The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances. From the diversity of Big Data variables comes many challenges that can be interesting to the researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter of linear regression model, one Covariate at a Time Multiple Testing OCMT. Moreover, the Euclidian Distance has been used as a comparison criterion among the three methods
Tau-P linear noise attenuation filter (TPLNA) was applied on the 3D seismic data of Al-Samawah area south west of Iraq with the aim of attenuating linear noise. TPLNA transforms the data from time domain to tau-p domain in order to increase signal to noise ratio. Applying TPLNA produced very good results considering the 3D data that usually have a large amount of linear noise from different sources and in different azimuths and directions. This processing is very important in later interpretation due to the fact that the signal was covered by different kinds of noise in which the linear noise take a large part.
The aim of the research is to identify the cognitive method (rigidity flexibility) of third-stage students in the collage of Physical Education and Sports Sciences at The University of Baghdad, as well as to recognize the impact of using the McCarthy model in learning some of skills in gymnastics, as well as to identify the best groups in learning skills, the experimental curriculum was used to design equal groups with pre test and post test and the research community was identified by third-stage students in academic year (2020-2021), the subject was randomly selected two divisions after which the measure of cognitive method was distributed to the sample, so the subject (32) students were distributed in four groups, and which the pre te
... Show MoreA seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus
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This study aims at identifying the impact of the application of IFRS 15 "Revenue from contracts with customers on the quality of financial reporting, through application to faculty members in the accounting departments of Iraqi universities and auditors. The problem of the study was the multiplicity of accounting rules and standards Which deals with the issues of revenue recognition , as well as the lack of consistency of most of them with the common framework of financial accounting, which results in low quality of financial reporting in the current financial statements, where the formulation of one hypothesis was the lack of relationship of significant significance The application of IFRS 15 "Recognition of rev
... Show MoreLinear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of models that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we dealt with the post optimality solution, or what is known as sensitivity analysis, using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model that will chan
... Show MoreMultiple sclerosis (MS) is a chronic, inflammatory, immune mediated disease of the central nervous system, mostly affecting young adults with mean age of 30 years, twice as high in women compared to men. The etiology of MS is not fully elucidated. MS symptoms are directly related to demyelination and axonal loss, along with other psychological symptoms, can result in functional limitations, disability and reduced quality of life (QoL). The QoL assessments in patients with a chronic disease may contribute to improving treatment and could even be of prognostic value. The goals of this study were to compare the QoL of Iraqi patients with relapsing remitting multiple sclerosis (RRMS),using three different diseas
... Show MoreMultiple eliminations (de-multiple) are one of seismic processing steps to remove their effects and delineate the correct primary refractors. Using normal move out to flatten primaries is the way to eliminate multiples through transforming these data to frequency-wavenumber domain. The flatten primaries are aligned with zero axis of the frequency-wavenumber domain and any other reflection types (multiples and random noise) are distributed elsewhere. Dip-filter is applied to pass the aligned data and reject others will separate primaries from multiple after transforming the data back from frequency-wavenumber domain to time-distance domain. For that, a suggested name for this technique as normal move out- frequency-wavenumber domain
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Water pollution is one of the global challenges that the society must address in the 21st century aiming to improve the water quality, reduce human pollutants and ecosystem health impacts. In phytotoxicity test, the plant of Iresine herbstii was exposed to remove nickel from simulated wastewater using two different ratios (mass of plant to the mass of nickel) (,Rp/Ni) for 21 days with sub-surface batch system. During the exposure period, the removal of Ni concentrations (2, 5 and 10 mg/L) for two mass ratio (2,800 and 34,000) were (83.6%, 77.2%, 78.0%) and (86.8%, 97% and 95.6%), respectively. final result of the rate was found that the highest removal occurred, 97%, at a mass ratio of 34,000 and
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