<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>
Duration of each developmental stage of the house dust mite Dermatophagoides pteronyssinus together with the mortality percentage were observed at a combination of five different temperatures namely 20C°, 22.5C°, 25C°, 27.5C° and 30C° and four different humidities namely 55%, 75%, 85% and 95% r. h. Results showed that temperature had the greatest effect on the life cycle period. The higher the temperature the shorter the life cycle was aid versa verea. On the other hand, humidity seems to be less effectiveness, though at the higher temperature and humidity no development was occured. Mortality among all temperatures and humidities appeared nearly the same, but at higher temperature and higher humidity and because of mould g
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The labeled research deal with (Entrepreneurship Organizations In the framework of strategic leadership practices: Field research in the Ministry of Oil), Search over the possibility of the influence of the practices of strategic leadership Which include
(Determine the strategic direction, The discovery of the fundamental estimators and maintain it, The development of the human capital, and Maintaining of an organizational culture influential, and Find a balanced regulatory Control) In a Entrepreneurship in its dimensions and its (innovation, risk, pre-emptive and independence) On group of heads of departments and authorities
... Show MoreProgression in Computer networks and emerging of new technologies in this field helps to find out new protocols and frameworks that provides new computer network-based services. E-government services, a modernized version of conventional government, are created through the steady evolution of technology in addition to the growing need of societies for numerous services. Government services are deeply related to citizens’ daily lives; therefore, it is important to evolve with technological developments—it is necessary to move from the traditional methods of managing government work to cutting-edge technical approaches that improve the effectiveness of government systems for providing services to citizens. Blockchain technology is amon
... Show MoreAHA Al-Hilali, AAH Hamid, The Journal of Law Research, 2022
The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode
... Show MoreSelf-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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