This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

In this research was to use the method of classic dynamic programming (CDP) and the method of fuzzy dynamic programming (FDP) to controlling the inventory in N periods and only one substance ,in order to minimize the total cost and determining the required quantity in warehouse rusafa principal of the ministry of commerce . A comparison was made between the two techniques، We found that the value of fuzzy total cost is less than that the value of classic total cost

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

            A field study aimed to improve  administrative performance of the Heads of Departments in Wasit University in light of the administrative functions, a questionnaire constructed was c of 38 items, as have been applied during the academic year 2014/2015 to a group of experts from the deans and assistants, professors and heads of departments using the Delphi method by two rounds the adoption rate of 90% and an agreement was numbered 30 experts and study reached important results have been analyzed and discussed according to fields of study, a planning, organization and direction.

This study focused on the various forms of violence that aged people encounter in their late life, the significance of taking measures that enhance not only the welfare for aged people but also the influence of early stage of life and how the old age effects on people experience throughout their live. Further, the importance of raising the awareness among communities to the extent of seriousness of old age in order to teach children the right habits and traditions, which are faded away over time.  The researcher indicated that raising the avenues of collaboration among home members, social organization, and all governmental facilities will support and provide a good treatment for this group of people.

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

This research aims to analyze and evaluate  the reality of the total quality management for the central laboratories by comparing systems of work in the laboratories of Al- Kadhimiya Didactic Hospital with the requirements of ISO 17025 to determine the degree of compatibility and the willingness to adapt to the requirements of the above specification and to show the ability of building an applicable quality management system and to identify problems and their mitigations and prevention to increase.

This study gains its importance from the importance of the labs which stems from the fact that the process of health is a set of interrelated activities, Medical examinations and tests con