This research aims to find out "the effectiveness of the self-questioning strategy in the achievement of students Phase III institutes of teacher preparation and decision-making in chemistry." The researcher follows approach quasi-experimental with a post-test, and the sample consisted of (27) from " Teachers Training Institute-AL-Byaa "in Directorate of Education Baghdad Karkh / 2 students divided into two unequal groups: experimental its number (14) students studied using reciprocal teaching strategy and control its number (13) students have studied in the usual way.The two groups were equivalent extraneous variables.

The researcher was prepare achievement test consist of 40 items was the adoption of a measure of decision-makin

Abstract

 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation

The present work determination astronomical ephemeris for satellites (determination position and velocity of satellite and orbital elements) in elliptical orbit where orbital elements in perigee point were known, therefore kepler's equation for elliptical orbit was solved by using Newton-Rephson method for numerical approximation.For the hyperbola orbit which represent orbit of shuttle (discovery join) far rang where solve kepler equation for hyperbola by use the same method pervious and then determination the coordinates of position and velocity for satellite or shuttle and the required programs are designing

درست عملية تحييد البلازميد لسبع عزلات محلية لبكتريا pneumoniae Klebsiella المتعددة المقاومة للمضادات الحيوية والمعزولة من حالات التهابات المجاري البولية باستخدام مادتي الـ Acridin .(SDS) Sodium dodecyl sulphate والـ orange أظهرت النتائج ان العزلات المحلية لجرثومة pneumoniae.K كانت ذات مقاومة عالية جدا ًاذ بلغت (%100) لمضادات امبيسيلين،ببراسيلين، اموكسيسيلين، بنسلين ج، تتراسايكلين، ارثرومايسين وجنتامايسين واظهرت مقاومة عالية (71–%86) لمضادات

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

              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 idea of ​​carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component  Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed