Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN model are identified as the ferritin and a gender variable. The higher results precision was attained by the multilayer perceptron (MLP) networks when we applied the explanatory variables as the inputs with one hidden layer, which covers 3 neurons, as the planned many hidden layers are with one output of the fitting NN model which is use in stages of training and validation beside the actual data. We used a portion of the actual data to verify the behaviour of the developed models, we find that only one observation is false prediction value. This mean that the estimation model has significant parameters to forecast the type of Covid cases (Covid or no Covid) .
In this paper, the researcher suggested using the Genetic algorithm method to estimate the parameters of the Wiener degradation process, where it is based on the Wiener process in order to estimate the reliability of high-efficiency products, due to the difficulty of estimating the reliability of them using traditional techniques that depend only on the failure times of products. Monte Carlo simulation has been applied for the purpose of proving the efficiency of the proposed method in estimating parameters; it was compared with the method of the maximum likelihood estimation. The results were that the Genetic algorithm method is the best based on the AMSE comparison criterion, then the reliab
... Show MoreIn the present work experiments were conducted to study the effect of solid loading (1,5 and 9 vol.%) on the enhancement of carbon dioxide absorption in bubble column at various volumetric gas flow rate (0.75, 1 and 1.5 m3/h) and absorbent concentration (caustic soda)( 0.1,0.5 and 1 M ). Activated carbon and alumina oxide (Al2O3) are used as solid particles. The Danckwerts method was used to calculate interfacial area and individual mass transfer coefficients during absorption of carbon dioxide in a bubble column. The results show that the absorption rate was increased with increasing volumetric gas flow rate, caustic soda concentration and solid loading. Mass transfer coefficient and interfac
... Show MoreCritical buckling and natural frequencies behavior of laminated composite thin plates subjected to in-plane uniform load is obtained using classical laminated plate theory (CLPT). Analytical investigation is presented using Ritz- method for eigenvalue problems of buckling load solutions for laminated symmetric and anti-symmetric, angle and cross ply composite plate with different elastic supports along its edges. Equation of motion of the plate was derived using principle of virtual work and solved using modified Fourier displacement function that satisfies general edge conditions. Various numerical investigation were studied to exhibit a convergence and accuracy of the present solution for considering some design parameters such as edge
... Show MoreThe ideas and principles formulated by Ibn-Jamaah in the field of education occupy a central place in the historical origins of education for Muslims. These views and principles have an active role in the educational reorganization that the Islamic world aspires to. These ideas have had a great impact on the educational process that had preceded the opinions of Russo, Pestalutzi, Fruel, Herbert, and Dewey. Moreover, we have seen that the Sheikh of Ibn-Jamaah has taken part in formulating the origins of education and leadership.
Nanoparticles of copper sulfide have been prepared by simple reaction between using copper nitrate with different concentrations ratio 0.1, 0.3, and 0.5 mM, thiourea by a simple chemical route. The prepared Nano powders have been deposited onto glass substrates by casting method at 60°C. The structure of the product Nano- films has been studied by x-ray diffraction, where the patterns showed that all the samples have a hexagonal structure of covellite copper sulfide with the average crystalline sizes 14.07- 16.51 nm. The morphology has been examined by atomic force microscopy, and field emission scan electron microscopy. The AFM images showed particles with almost spherical and rod shapes with average diameter sizes of 49.11- 90.64 nm.
... Show MoreCobalt substituted nickel copper ferrite samples with general formula Ni0.95-xCoxCu0.05Fe2O4, where (x= 0.00, 0.01, 0.02, 0.03, 0.04 and 0.05) were prepared by solid-state reactions method at 1373 K for 4h. The samples prepared were examined by X-ray diffraction (XRD(, atomic force microscope (AFM), Fourier transform infra-red spectroscopy (FTIR) and Vickers hardness. X-ray diffraction patterns confirm the formation of a single phase of cubic spinel structure in all the prepared samples . XRD analysis showed that the increase in the cobalt concentration causes an increase in the lattice constant, bulk density (ρm) and the x-ray density (ρx), whereas porosity (p) and crystallite size (D) decrease. The Topography of the surface observed
... Show MoreThis paper is focused on studying the effect of cutting parameters (spindle speed, feed and depth of cut) on the response (temperature and tool life) during turning process. The inserts used in this study are carbide inserts coated with TiAlN (Titanum, Aluminium and Nitride) for machining a shaft of stainless steel 316L. Finite difference method was used to find the temperature distribution. The experimental results were done using infrared camera while the simulation process was performed using Matlab software package. The results showed that the maximum difference between the experimental and simulation results was equal to 19.3 , so, a good agreement between the experimental and simulation results was achieved. Tool life w
... Show MoreThe aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette
... Show MoreDust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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Abstract
Due to the lack of previous statistical study of the behavior of payments, specifically health insurance, which represents the largest proportion of payments in the general insurance companies in Iraq, this study was selected and applied in the Iraqi insurance company.
In order to find the convenient model representing the health insurance payments, we initially detected two probability models by using (Easy Fit) software:
First, a single Lognormal for the whole sample and the other is a Compound Weibull for the two Sub samples (small payments and large payments), and we focused on the compoun
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