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 model. Having been in this research compare these methods form a model for additive function to some nonparametric function. It was a trade-off between these process models based on the classification accuracy by misclassification error, and estimation accuracy by the root of the mean squares error: RMSE. It was the application on patients with diabetes data for those aged 15 years and below are taken from the sample size (200) was withdrawn from the Children Hospital in Al-Eskan / Baghdad.
This paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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This study aimed to determine obesity level of some population in Baghdad by using Bio-electrical impedance analysis (BIA) and compared with anthropometric measurements such as body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR). Statistical analysis results of linear correlation coefficients for obesity indicators showed that BIA correlation 0.92 was most significant and reliable for obesity measurement.
Results of BIA method for age group 20-29 years showed that 44.4% of females were healthy body while 37.8% of males suffer from increased body fat. Results of age group 30-39 year showed that 32.6 of females were in healthy body and 42% of males were obese. In case age group 40-4
... Show MoreA new panel method had been developed to account for unsteady nonlinear subsonic flow. Two boundary conditions were used to solve the potential flow about complex configurations of airplanes. Dirichlet boundary condition and Neumann formulation are frequently applied to the configurations that have thick and thin surfaces respectively. Mixed boundary conditions were used in the present work to simulate the connection between thick fuselage and thin wing surfaces. The matrix of linear equations was solved every time step in a marching technique with Kelvin's theorem for the unsteady wake modeling. To make the method closer to the experimental data, a Nonlinear stripe theory which is based on a two-dimensional viscous-inviscid interac
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In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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The research is summarized in the construction of a mathematical model using the most common methods in the science of Operations Research, which are the models of transportation and linear programming to find the best solution to the problem of the high cost of hajj in Iraq, and this is done by reaching the optimum number of pilgrims traveling through both land ports and the number Ideal for passengers traveling through airports by Iraqi Airways, instead of relying on the personal experience of the decision-maker in Hajj and Umrah Authority by identifying the best port for pilgrim's travel, which can tolerate right or wrong, has been based on scientific methods of Operations Research, the researcher built two mathematical models
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The purpose of this study is to investigate learners' listening comprehension problems with Englishlectures. The study was guided by research question (What are the listening comprehension problems learners have with lectures in English).Furthermore; the main significant goal were declared through conducting this study, as well as providing some procedures of distribution the questionnaire of the study.Moreover, it presents several definitions of listening. This study definitely depends on questionnaire instrument to gathering the required data. The participants of the study were 30 learners completed their secondary school and joined at the college. Based on the findings among the five factors (text, speaker, task, environment, and list
... Show MoreNet pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.
This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.
The Mishrif formation was
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