Face recognition is a biometric technique that can be used for a variety of purposes, such as national security, access control, identity fraud, banking, and finding missing children. Faces are highly dynamic and facial features are not always easily extracted, which can lead to discarding textural information like the smoothness of faces, a hairstyle that, might contain strong identity information. In addition, brightness, scale, and facial expressions play a significant role in the face-recognizing process. Therefore, face recognition is considered as a difficult problem. To figure out this problem effective methods using databases techniques are needed. This paper describes face recognition methods and their structure. Based on Wen Yi Zhao and Rama Chellappa work the face recognition methods are divided into three groups: a holistic approach, feature-based approach, and hybrid approach, where Principal Component Analysis PCA, a holistic approach method, is presented as a mathematical technique that can assist the process of face recognition. Also, the paper shows how the PCA is used to extract facial features by removing the principal components of the available multidimensional data.

Counting the number of people in many estimation systems, such as still images or video frames, is a buoyant research area that is challenging in the field of computer vision. It plays a considerable role in a variety of applications, such as security, management, education, and commerce. The purpose of this paper is to suggest a system to estimate the number of people in digital still images based on the Face Detection method. This system composed of two parts: face detection and counting of detected faces. In the detection step, the Skin Color Face Detection method was applied on the input of a digital still image. In the counting part, the obtained detected faces by the Skin Color Face Detection method have counted to estimate the number of people in an input color image with simple software and simple low-cost hardware. The skin color face detection algorithm was tested using 133 images from the People Image Groups dataset, which contains about 2573 color images of people, to test the proposed system. based on the obtained results, the best precision achieved of the proposed Skin Color face detection algorithm was 85%

Counting the number of people in many estimation systems, such as still images or video frames, is a buoyant research area that is challenging in the field of computer vision. It plays a considerable role in a variety of applications, such as security, management, education, and commerce. The purpose of this paper is to suggest a system to estimate the number of people in digital still images based on the Face Detection method. This system composed of two parts: face detection and counting of detected faces. In the detection step, the Skin Color Face Detection method was applied on the input of a digital still image. In the counting part, the obtained detected faces by the Skin Color Face Detection method have counted to estimate the number of people in an input color image with simple software and simple low-cost hardware. The skin color face detection algorithm was tested using 133 images from the People Image Groups dataset, which contains about 2573 color images of people, to test the proposed system. based on the obtained results, the best precision achieved of the proposed Skin Color face detection algorithm was 85%

Traditional education depends on a set of basic elements, the most important of which are the educational curriculum, the lecturer, and the student, but these basic elements have been added to a new element in distance education, which is the electronic environment. During the COVID19 pandemic that began at the end of 2019 and the rapid transformation from traditional education to distance education and the involvement of distance education in implementing pre-prepared educational plans. This rapid transformation, in which the elements of education were not developed and not prepared in advance, led to the emergence of some problems in the educational outputs. Distance education, although its basic elements are the same as those of traditional education, the method of implementing it differed by introducing a new essential element, which is the electronic environment through which educational plans are implemented. In this research paper, the most important and influential actors in the educational process of distance learning and the problems resulting from this rapid transformation will be studied, then find appropriate solutions to keep pace with the development in the educational process, through an evaluation study of the experience of the Faculty of Science at Gharyan University. The results of this research will be useful to implement changes in the educational system and to meet the requirements of modern educational standards for higher education.

The effect of Traverse speed on the microstructures of friction stir welded 6 mm thick austenitic stainless steel (304) plate has been investigated. Quantitative optical, high resolution scanning electron microscopy and Vickers hardness have been used to qualify and examine the microstructure through the plate cross section. The tool material was used is Tungsten Rhenium. For this work, friction stir welding was performed at rotation speed of 350 revolution per minutes (rpm) and traversing speed from 150 to 250 millimeter per minutes (mm/min) with an interval of 50 mm/min. Fine austenite has been observed in the stir zone, indicating that dynamic recrystallisation with no phase transformation occurred during FSW. The hardness profile is relatively homogeneous with slightly higher values in the stir zone than that of the base metal, suggesting that deformation and the cooling rate are dominant in the FSW process.