<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, comes in second place with a gross ratio of 91%. Furthermore, Bayesian ridge (BR), linear regressor (LR), and stochastic gradient descent (SGD), with mean square error and with accuracy ratios of 84.365%, 84.363%, and 79%. As a result, the performance precision of these regression models yields. The interaction framework was designed to be a straightforward tool for working with this paradigm. This model is a valuable tool for establishing strategies to counter the swiftness of climate change in the area under study.</span>
Purpose: The research seeks to develop the implications of intellectual human capital, and social capital in business organizations, and will be accomplished on three levels, the first level (the level of description) to identify, diagnose and display content philosophical Strategic Human Resource Management at the thought of modern administrative represented by human capital and Ras social capital. The second level (level of analysis) and the analysis of the extent of the impact of alignment between human capital, and social capital in the organizational strength of the organizations. The third level (Level predict) the formulation of a plan to strengthen the organizational strength in business organizations and to develop speci
... Show MoreAs COVID-19 pandemic continued to propagate, millions of lives are currently at risk especially elderly, people with chronic conditions and pregnant women. Iraq is one of the countries affected by the COVID-19 pandemic. Currently, in Iraq, there is a need for a self-assessment tool to be available in hand for people with COVID-19 concerns. Such a tool would guide people, after an automated assessment, to the right decision such as seeking medical advice, self-isolate, or testing for COVID-19. This study proposes an online COVID-19 self-assessment tool supported by the internet of medical things (IoMT) technology as a means to fight this pandemic and mitigate the burden on our nation
The United States has stood by Iraq and supported militarily and morally, but the relationship did not quickly be strained again before August 1990, when the oldest former political system in Iraq after Iraqi troops entered the territory of Kuwait, the United States stood beside Kuwait because the two parties link military ties opted States United to support the Kuwaiti side relying on the resolutions passed by the UN security Council, the United States and found in this issue right opportunity to execute the mechanics of meddling in Iraqi affairs and the various means of political, economic, military, and methods for dealing with Iraq, especially after finding the impediment standing in front of the implementation of its goals The strat
... Show MoreThis study represents an attempt to develop a model that demonstrates the relationship between HRM Practices, Governmental Support and Organizational performance of small businesses. Furthermore, this study assay to unfold the socalled “Black Box” to clarify the ambiguous relationship between HRM practices and organizational performance by considering the pathway of logical sequence influence. The model of this study consists two parts, the first part devoted to examining the causal relationships among HRM practices, employees’ outcomes, and organizational performance. The second part assesses the direct relationship between the governmental support and organizational performance. It is hypothesized that HRM practices positively influ
... Show MoreIn this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.
In this research The study of Multi-level model (partial pooling model) we consider The partial pooling model which is one Multi-level models and one of the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly among the stations in Iraq. We use Akaik′s Informa
... Show MoreConcerns about the environment, the cost of energy, and safety mean that low-energy cold-mix asphalt materials are very interesting as a potential replacement for present-day hot mix asphalt. The main disadvantage of cold bituminous emulsion mixtures is their poor early life strength, meaning they require a long time to achieve mature strength. This research work aims to study the protentional utilization of waste and by-product materials as a filler in cold emulsion mixtures with mechanical properties comparable to those of traditional hot mix asphalt. Accordingly, cold mix asphalt was prepared to utilize paper sludge ash (PSA) and cement kiln dust (CKD) as a substitution for conventional mineral filler with percentages ranging fro
... Show MoreIn this research The study of Multi-level model (partial pooling model) we consider The partial pooling model which is one Multi-level models and one of the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly among the stations in Iraq. We use Akaik′s Informa
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