journal port science research

The research aims to identify the extent of the application of the Iraqi University
College of Education NCATE standards, the researcher used the descriptive method has been
selected research community has reached (107) teaching and to achieve the goal of the research
prepared a questionnaire consisting of (49) paragraph distributed on (6) criteria and the researcher
verified its sincerity The results of the research indicated that the degree of application of the College
of Education NCATE criteria came to a high degree for both the fifth standard and

Automatic analysis of facial expressions is rapidly becoming an area of intense interest in
computer vision and artificial intelligence research communities. In this paper an approach is presented for
facial expression recognition of the six basic prototype expressions (i.e., joy, surprise, anger, sadness, fear,
and disgust) based on Facial Action Coding System (FACS). The approach is attempting to utilize a
combination of different transforms (Walid let hybrid transform); they consist of Fast Fourier Transform;
Radon transform and Multiwavelet transform for the feature extraction. Korhonen Self Organizing Feature
Map (SOFM) then used for patterns clustering based on the features obtained from the hybrid transform
above. The result shows that the method has very good accuracy in facial expression recognition. However,
the proposed method has many promising features that make it interesting. The approach provides a new
method of feature extraction in which overcome the problem of the illumination, faces that varies from one
individual to another quite considerably due to different age, ethnicity, gender and cosmetic also it does not
require a precise normalization and lighting equalization. An average clustering accuracy of 94.8% is
achieved for six basic expressions, where different databases had been used for the test of the method.