Multilevel models are among the most important models widely used in the application and analysis of data that are characterized by the fact that observations take a hierarchical form, In our research we examined the multilevel logistic regression model (intercept random and slope random model) , here the importance of the research highlights that the usual regression models calculate the total variance of the model and its inability to read variance and variations between levels ,however in the case of multi-level regression models, the calculation of  the total variance is inaccurate and therefore these models calculate the variations for each level of the model, Where the research aims to estimate the parameters of this m

In a resource-limited world, there is an urgent need to develop new economic models, from the traditional unsustainable industrial model of product consumption and disposal, to a new model based on the concepts of sustainability in its comprehensive sense, the so-called circular economy, using fewer resources in manufacturing processes and changing practices in product disposal to waste, by removing its use, recycling and manufacturing to start another manufacturing process. In an era of intense competition in domestic and global markets, the importance of the circular economy is highlighted in its ability to strengthen the competitiveness of enterprises in those markets, by reducing the cost and increasing the quality of the pro

Research indicates that the second half of the twentieth century marked large interests in the service industry by government and private organizations in that one, and the service industry has become the bedrock of plans in achieving economic and social development. From this standpoint felt specialists and researchers the importance of transport modes, including rail, which should be available between Almnltq Civil populated as services organized by the competent authorities to achieve the active participation of citizens in economic and social development in the region and that the term services means economic activities, which are the results Pollack concrete such as accepting the situation and satisfaction them or satisfacti

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

The use of artificial intelligence (AI) technology is rapidly expanding in nursing and society. However, its use in healthcare comes with a number of challenges and concerns. The authors of this article use the sociotechnical model to consider the expanding use of AI in nursing and healthcare from a global perspective. Select references from the literature are used to support this important discussion for nurses and other healthcare professionals. Artificial intelligence is a major innovation that, if used properly, can reduce errors and improve efficiency and healthcare quality. It has also been shown to increase patient support, healthcare access and patient care. Here the authors address some of the limitations and challenges of

This study attempts to test the interactive role played by organizational agility in enhancing the effect of organizational anomie on the behavior of planned human resources. The study of organizational anomie has increased because of the moral and legal pressures facing the organization by the external environment within its framework. To adapt to all external developments faced by these organizations, the behavior of human resources planned reflects the ability of individuals to control their behavior in different situations and situations that face them in the work.

The problem of the research indicates that there is a clear lack of understanding of what is meant by the variables studied in the sample