Slow learning becomes a problem in the present , where it comprises ratio musnt ignore in every school . So , its one of education problems facing by parents and teachers .

Slow learning subject regard of new subject attract the attention in the last years of the 20^th century where the attention was focusing on the other disabilities but the existence of number of healthy children suffering from Learning problems attract the attention of the researchers .

So , this study aims at recognizing the degree of self , concept among slow learner students and the differences significance of self concept according to sex and academic degree of parents variables.

Because there is not tool , the researcher build a

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

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

The human perception of science and knowledge is affected by the personal point of view, thus giving it its religious, mental and emotional dimensions to make that perception an effective tool for realizing the truth comprehensively in the delivery of knowledge to the depths of the human soul. The later is composed of multiple factors, which contributes to the human self-development with dimensions beyond the limits of mental logic and the perception of material and emotional situations. That knowledge in the perception of Islamic virtue, which must characterize each Muslim.
Human beings have been striving for knowledge and the understanding of the universe in which they live. For centuries, mankind has acquired knowledge directly an

e current research aims to know the effect of fishbone strategy on achievement of chemistry and visual thinking among middle school students, the research sample consisted of 89 students divided into two experimental groups consisting of 44 students who studied fishbone strategy, and a control group that consisted of 45. A student studied in the usual way; the two groups were rewarded in a number of variables, and the researcher built two tools for the research: the first is an achievement test consisting in 30 paragraphs, and the second is a visual thinking test consisting in 18 paragraphs. Keywords: Chemistry, fishbone, seven grade, students, visual thinking..

Despite recent attempts to improve safety in the construction sector, this sector is considered dangerous and unsafe. Iraq is one of the emerging nations that suffers from a lack of construction safety management. In 2018, the construction sector in Iraq was responsible for 38% of all industrial accidents. Creating a safety program minimizes this problem by making safety an intrinsic part of construction projects. As a result, this article aims to identify the crucial safety factors that affect the safety performance in Iraqi construction projects. After conducting a critical literature review of the related literature, a list of 35 sub-factors classified into nine categories of main factors was chosen to rank each facto