The problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, 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-

A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

Background: spontaneous abortion constitutes one of the most important adverse pregnancy outcomes affecting human reproduction, and its risk factors are not only affected by biological, demographic factors such as age, gravidity, and previous history of miscarriage,but also by individual women’s personal social characteristics, and by the larger social environment. Objective:To identifyEnvironmental effects on Women's with Spontaneous Abortion. Methodology:Non-probability(purposive sample)of(200) women, who were suffering from spontaneous abortion in maternity unitfrom four hospitals at Baghdad City which include Al-ElwiaMaternity Teaching Hospital, and Baghdad Teaching Hospital at Al-Russafa sector. Al–karckhMaternityHospita

     The concept of a small f- subm was presented in a previous study. This work introduced a concept of a hollow f- module, where a module is said to be hollow fuzzy when every subm of it is a small f- subm. Some new types of hollow modules are provided namely, Loc- hollow f- modules as a strength of the hollow module, where every Loc- hollow f- module is a hollow module, but the converse is not true. Many properties and characterizations of these concepts are proved, also the relationship between all these types is researched. Many important results that explain this relationship are demonstrated also several characterizations and properties related to these concepts are given.

The majority of used clothes represented a passion for brilliant
appearance and could be a reason for hiding body defects , as to avoid
criticism .
This may lead to purchase and wear un healthy or uncomfortable clothes
such as tide .As to appreciate the differences between wearing healthy clothes or
otherwise .
The study was carried out to assess healthy cloth awareness for university
girls as related to possibility of being subjected to harm caused by wearing tide
clothes .
The measurement items was determined and numbered ( 23 ). The answer
for these scale criteria was ( Always , Sometime ,Never ) for the weights (3,2,1)
. The scale was applied to a randomly selected sample of research community
that

In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.