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

Multiple 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

Background: Color stability of glass ionomers (GIs) could be affected by many factors such as pH and consumption of liquid medications like antibiotics. Most common antibiotics used during childhood are amoxicillin suspension (AM.S) and azithromycin suspension (AZ.S) which have acidic and basic pH respectively. Aim: to evaluate and compare the effect of AM.S and AZ.S on color stability of nano resin-modified GI. Methods: Thirty disc of nano resin-modified glass ionomer (2mm height x 4mm diameter) were divided into three groups (n=10 for each) and independently exposed to AM.S, AZ.S, and artificial saliva (A.S.). Color stability was evaluated in triplicate by VITA Easyshade® before and after three immersion protocols, repeated over a thr

Background: Color stability of glass ionomers (GIs) could be affected by many factors such as pH and consumption of liquid medications like antibiotics. Most common antibiotics used during childhood are amoxicillin suspension (AM.S) and azithromycin suspension (AZ.S) which have acidic and basic pH respectively. Aim: to evaluate and compare the effect of AM.S and AZ.S on color stability of nano resin-modified GI. Methods: Thirty disc of nano resin-modified glass ionomer (2mm height x 4mm diameter) were divided into three groups (n=10 for each) and independently exposed to AM.S, AZ.S, and artificial saliva (A.S.). Color stability was evaluated in triplicate by VITA Easyshade® before and after three immersion protocols, repeated over

Alice Walker's novel The Color Purple1983, whose events take place in the rural Georgia and addresses the most important issues in the early 20^thcentury; like male dominant society and women submission to men, weaves a mosaic picture of male-female relationships. Black men like Alphonso, Albert and Harpo are portrayed as oppressors, cruel and they exercise power and violence over their wives and daughters. Through the negative portrayal of black male characters, Walker is accused to be a men hating writer because she ''Views oppression as an essentially masculine activity which springs from the male's aggressive need to dominate. In the novel, man is the premium mobile, the one by whom and t

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

Quantitative real-time Polymerase Chain Reaction (RT-qPCR) has become a valuable molecular technique in biomedical research. The selection of suitable endogenous reference genes is necessary for normalization of target gene expression in RT-qPCR experiments. The aim of this study was to determine the suitability of each 18S rRNA and ACTB as internal control genes for normalization of RT-qPCR data in some human cell lines transfected with small interfering RNA (siRNA). Four cancer cell lines including MCF-7, T47D, MDA-MB-231 and Hela cells along with HEK293 representing an embryonic cell line were depleted of E2F6 using siRNA specific for E2F6 compared to negative control cells, which were transfected with siRNA not specific for any gene. Us