This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduced by using an algorithm that calculates the predicted value. The utilization of machine learning models that have been trained on massive datasets, the implementation of strategies for correct face alignment, and the utilization of expected value regression formulations have all been significantly incorporated into the suggested approach. The model’s performance is optimized and improved in this study by utilizing several distinct classifiers, increasing the effectiveness of explicit expectations. We aimed to optimize the selection of classifiers to minimize energy consumption while achieving a mean absolute error of 2.08 (average) and a power usage of 2700 W.
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In this paper, the exact solutions of the Schlömilch’s integral equation and its linear and non-linear generalized formulas with application are solved by using two efficient iterative methods. The Schlömilch’s integral equations have many applications in atmospheric, terrestrial physics and ionospheric problems. They describe the density profile of electrons from the ionospheric for awry occurrence of the quasi-transverse approximations. The paper aims to discuss these issues.
First, the authors apply a regularization meth
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Based on nonlinear self- diffraction technique, the nonlinear optical properties of thin slice of matter can be obtained. Here, nonlinear characterization of nano-fluids consist of hybrid Single Wall Carbon Nanotubes and Silver Nanoparticles (SWCNTs/Ag-NPs) dispersed in acetone at volume fraction of 6x10-6, 9x10-6, 18x10-6 have been investigated experimentally. Therefore, CW DPSS laser at 473 nm focused into a quartz cuvette contains the previous nano-fluid was utilized. The number of diffraction ring patterns (N) has been counted using Charge - Coupled- Device (CCD) camera and Pc with a certain software, in order to find the maximum change of refractive index ( of fluids. Our result show that the fraction volume of 18x10-6 is more nonli
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The world's renewable energy sources have taken on great importance, for its cleanness and its environmental effects as well as being a renewable source, Increased demand for fossil energy sources is also causing global warming and climate change. Iraq is an appropriate area for renewable energy This study shows that renewable alternative energy has not been used sufficiently enough at present. But this energy can play an important role in the future of renewable energy in Iraq. This research aims to study the renewable energy in Iraq (solar energy) and it is appropriate to develop this alternative energy for crude oil, which is characterized by the use of the most appropriate and less economical and more environmentally friendly. Solar
... Show More. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
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The emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t
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The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.
In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes. Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo
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