Objective: To assess the Impact of Socio-economic status on age at menarche among secondary school students at
AL-Dora city in Baghdad, Iraq.
Methodology: This is a cross sectional study with multi-stage sampling was carried out during the period from the
3
th of December2013 to 12th of March 2014. The Sample comprised of 1760 girls, 1510 girls from urban area and
250 from rural area was included in the study. In first stage, selection of schools was done, and one class was
selected randomly from each level of Education, The data collection through a special questionnaire which Contain
the age of girl by year, class level, birth order, number of household, number of rooms, residency (urban/rural),
education level

Abstract:

 The underlying objective of the international standard No. (6) to assist in accounting applications for the extractive industries, taking into consideration the goals and objectives contained in the sixteenth of the private International Accounting Standards criterion accounting for land, machinery and equipment, as well as Standard No. axes (38) relating to intangible assets, and in order to create a vision of a comprehensive development needs oil in order to exact evaluation of policies related to the particular needs and draw a comprehensive frameworks with respect to treatment of expenditures and revenues in the oil production industry, is also interested in Standard No. (6) within the primary objectiv

Background: Body image is one of the most important psychological factors that affects adolescents’ personality and behavior. Body image can be defined as the person’s perceptions, thoughts, and feelings about his or her body.

Objectives: to identify the prevalence of body image concerns among secondary school students and its relation to different factors.

Subjects and methods: A cross-sectional study conducted in which 796 secondary school students participated and body shape concerns was investigated using the body shape questionnaire (BSQ-34).

Results: The prevalence of moderate/marked concern was (21.6%). Moderate/ marked body shape concern was significantly associated

Abstract The goal of current study was to identify the relationship between addiction of self-images (Selfie) and personality disorder of narcissus, and the difference of significance the relationship between addiction self-images (selfie) and personality disorder narcissus at students of Mustansiriya university, addiction self- images (selfie) defined: a photograph that one has taken of oneself, typically one taken with a smartphone or webcam and shared via social media, edit and down lowed to social networking sites, and over time, the replacement of normal life virtual world, which is accompanied by a lack of a sense of time, and the formation of repeated patterns increase the risk of social and personal problems. To achieve the goals

      TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv