Abstract

The Purpose of This Research is The  Main Factors  In out Comes Phenomena From Primary School Which in Creased in Lost Period in Iraq And to Find Solutions to The This Problem.

In Order to Achieve Al The Aim The Research Choose a Systematic Random Sample of School Records For Students in Some Primary Schools in Karkh and Rusafa and Year of Study (2010-2015) and Size (40) Samples, included  (16) Variable , Collected in Form Prepared by The Research As a Way to Analyze The Data.

Remember to Summarize The (6) Main components Pay a Student to Drop out of Primary Schools in The Province of Baghdad are Arranged As Follows:

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

Abstract

The resources-based introduction in the study of business organizations is increasingly dealing in the study of the human capacities and the best ways to develop them and changing the resources of the organization to be essential and competent to face the business challenges. Today’s organizations need crucial practices to face those challenges and the influences of those practices which take into consideration the importance of developing the entrepreneurship inside the organization. Those practices are called “High Performance Work Systems” which is denoted by “HPWS” and defined as the practices of human resources management which help in acquiring func

Modern communication and media technology has pioneered new horizons and curried out deep changes in the various fields of social life, It effected enormously human communication as well.
Content one Who late the developments which have effected the social relations ،due to the new media ،especially Face book ,will certainly notice the far cry changes of the social relation net which has been effected ,in a way or another ،the accelerated development ،under the appearance of the so called the virtual society .
Face book has embodied the means – communication ,which has become an important turn point in the social communication .
It is the point the present paper tries to expose an discuss by a field study curried on a sam

The research aims to identify intelligence spiritual among a sample of students Baghdad University as well as to identify the differences between students in intelligence spiritual according to variable type (male - female), and variable area of ​​study (Science - a human) and variable (First grade - fourth grade), The research sample consisted of (300) students, were applied scale search - a spiritual Intelligence Scale (prepared by the researcher), has resulted in the search results for: -

The students of the University of Baghdad (sample) enjoyed a high level of spiritual intelligence.
- There are no differences between males and females in the spiritual intelligence.
- There

ABSTRACT Background: work-related musculoskeletal disorders represent an important occupational health issues among dentists especially neck and low back complaints. Biomarkers of tissue damage as results of occupational physical demands could be used for detection of work related musculoskeletal disorders. Aim: The aim of this study was to assess work- related musculoskeletal disorders, physical work load index, selected salivary biomarkers (Creatine kinase and C - reactive protein) and to find the relation among them. Subjects and Methods: Study participants are consisted of 112 dentists. They were selected from college of dentistry /Baghdad University, health care center in Bagdad city. They were of both gender and aged between 40-45 yea

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu