The sentence is one building unit in a music that has a full  meaning which in the end takes a long silence .The sentence bases made the sentences with  intransitive verb ( non connection ) and the sentences are   made with general verb (connection ) .The sentence parts :Verbal sentence –supportive sentence , sentence without a verb .

The method of divide the sentence into these syntax  units ( face division ) or (analysis and to each of the syntax units resulted from dividing the sentence to sections made to the end the characterizes the  smaller syntax units ,the words .The method of analyze the surface structure of Persian language sentence  is exchange method.   &nbsp

This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

The aim of the research is to identify the imaginative thinking skills included in the content of the chemistry textbook for fifth-grade students in biological sciences at the preparatory stage, which is approved by the Ministry of Education, General Directorate of Curricula in the academic year 2020-2021. To achieve the objective of the study, the researcher depends on the previous studies in the field and content of imaginative thinking skills for preparing a list of skills that includes (3) essential skills and (11) sub-skills and (28) items related to all skills. The researcher adopted the analytical descriptive approach because of its appropriation of the goals of the research. Then the researcher analyzed the content of the book de

This research aims to study the important of the effect of analysis of covariance manner for one of important of design for multifactor experiments, which called split-blocks experiments design (SBED) to deal the problem of extended measurements for a covariate variable or independent variable (X) with data of response variable or dependent variable Y in agricultural experiments that contribute to mislead the result when analyze data of Y only. Although analysis of covariance with discussed in experiments with common deign, but it is not found information that it is discussed with split-Blocks experiments design (SBED) to get rid of the impact a covariance variable. As part application actual field experiment conducted, begun at

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

 Aleksandr Isayevich Solzhenitsyn was born in 1918 in Kislovodsk. His father was educated, and despite his peasantry origin, he got a university degree. Unfortunately, however, Solzhenitsyn could not recognize his father, for he died before his birth.

Solzhenitsyn was accused of being an opponent to the Soviet Union due to his activities of that time. He was exiled to a forced labour camp for eight years, on the surroundings of Moscow. He spent three years in Kazakhstan, and was sent to the life exile. He was set free in 1956. He worked as a teacher in in rural schools in Vladimir and then in Rezhran. 

His greatest works were in the reign of Kherchov, and in 1962 appeared his story under the title of "One day in

              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

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise