The demand for expatriate labor to Iraq increased after 2003 as a result of the openness that Iraq experienced, but this expatriate labor, which was requested at an increasing rate, has had economic, social, and political effects on the Iraqi economy in general, and the Iraqi labor market in particular. This is due to the high rates of unemployment, as most of these expatriate workers cause competition to local labor, and thus cause repercussions on the Iraqi economy as a whole, except for those expatriate workers coming with companies working in the oil sector. Iraq's GDP

Research problem:
Problem of current research can determine the dimensions to answer the following question: The effect of teaching using the six thinking hats on academic achievement for students in the second grade average in the subject of Family Education. The importance of research: research is gaining importance in terms of:
1. That this research is the first of its kind in the researcher's knowledge _ which deals with the teaching of Family Education by using the six hats, the researcher hopes to fill a gap in the educational field and serve in other studies serve the materials home economics. 2. Keep pace with the new field of modern education and strategies. 3. Highlight on the educational strategy in the field of creative

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci