Factor analysis is distinguished by its ability to shorten and arrange many variables in a small number of linear components. In this research, we will study the essential variables that affect the Coronavirus disease 2019 (COVID-19), which is supposed to contribute to the diagnosis of each patient group based on linear measurements of the disease and determine the method of treatment with application data for (600) patients registered in General AL-KARAMA Hospital in Baghdad from 1/4/2020 to 15/7/2020. The explanation of the variances from the total variance of each factor separately was obtained with six elements, which together explained 69.266% of the measure's variability. The most important variable are cough, idleness, fever, headach

his study aims to determine most stable isobar from some isobaric elements with mass number (A= 50-65 & 180-195). This aim achieved by, firstly: plot mass parabolas for these isobaric family, second: calculated the atomic number for most stable isobar (ZA) value. To plot the mass parabola, the binding energy (B.E) calculated from semi empirical formula for these isobars. The mass number (A) plotted as a function to the (ZA) for each range; we get a linear relationship between them. An empirical formula for the most stable isobar has been developed from this linear dependence. From the results, we can see that mass parabolas for isobaric elements with odd mass number (A) are different from the mass parabolas of even mass number (A) isobars,

This study is descriptive and theory of Dawn syndrome as the problem of research lies in the need to identify the identification of the causes of Dawn syndrome and its symptoms and methods of dealing with it, which has become a problem that needs treatment, especially after the numbers have become high in Iraq, which has not yet taken the necessary importance for treatment and care.

The objectives of the research were summarized in the identification of the most important causes of Dawn syndrome and its symptoms and diagnosis and ways or methods of dealing with people with Dawn syndrome in order to develop therapeutic plans for him.

This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that