Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

Objective: The aim of this study is to identify the impact of training education program applied on
nurse-midwife practice concerning care during third stage of labor in labor room. Examine the
relationship between their knowledge regarding practices and some Demographic information’s.
Methodology: A quasi-experimental design conducted on non-probability (purposive) sample of fifty
two nurse-midwives selected during period from3
th August to 10thNovember 2011. The study is
conducted at the Ministry of Health (Baghdad health directorate in Al-Karhk and Al-Risafa sector) in
four hospitals. The questionnaire form is consisted of three parts which included demographic data,
knowledge concerning practice during third

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

تناولنا في هذه الدراسة التأكيد على تطوير المناهج الدراسية بأتجاه تنمية قيم التسامح والتعايش السلمي ، لان ثقافة التسامح باتت من الضرورات الملحة التي يفرضها الواقع الراهن لمواجهة العنف المجتمعي ، مما يوجب الحرص على ترسيخ القيم الانسانية ، لان التسامح من الصفات التي تحبها النفوس وتنجذب اليها القلوب .

والقيم الاخلاقية والسلوكية كالتسامح وغيرها ، من الامور الرئيسية لعمليتي التربية والتعليم في المدارس وال

The research aimed at designing teaching sessions using the self-scheduling strategy with a competitive style in learning handball as well as identifying differences between pre and post tests in both groups in learning short and long passes in handball. The researchers used the experimental method on 2nd-grade secondary school students. The researchers concluded using the self-scheduling strategy due to its positive effect on learning short and long handball passes in handball. Finally, the researchers recommended applying strategies and styles in teaching different school levels as well as making similar studies using teaching strategies and styles for learning handball skills in students.

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac