The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

The Purpose of this research is a comparison between two types of multivariate GARCH models BEKK and DVECH to forecast using financial time series which are the series of daily Iraqi dinar exchange rate with dollar, the global daily of Oil price with dollar and the global daily of gold price with dollar for the period from 01/01/2014 till 01/01/2016.The estimation, testing and forecasting process has been computed through the program RATS. Three time series have been transferred to the three asset returns to get the Stationarity, some tests were conducted including Ljung- Box, Multivariate Q and Multivariate ARCH to Returns Series and Residuals Series for both models with comparison between the estimation and for

Abstract

In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications  in order  to get mean square error and used it to make compare , simulation experiment  contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif

In this study, geopolymer mortar was designed in various experimental combinations employing 1% micro steel fibers and was subjected to different temperatures, according to the prior works of other researchers. The geopolymer mortar was developed using a variety of sustainable material proportions (fly ash and slag) to examine the influence of fibers on its strength. The fly ash weight percentage was 50%, 60%, and 70% by slag weight to study its effect on the geopolymer mortar's properties. The optimal ratio produced the most significant results when mixed at a 50:50 ratio of fly ash and slag with 1% micro steel fibers at curing temperature 240oC for 4 hours through two days. The compressive strength of the geopolymer mortar increas

The research aims to shed light on the possibility of measuring the intellectual capital in the Iraqi insurance company using accounting models, as well as disclosing it in the financial statements of the company, where human capital was measured using the present value factor model for discounted future revenues and the intellectual value-added factor model for measuring structural capital It was also disclosed in the financial statements based on the theory of stakeholders. The research problem lies in the fact that the Iraqi insurance company does not carry out the process of measuring and disclosing the intellectual capital while it is considered an important source for the company’s progress in the labor market recently. T

Background: One of the major problems in endodontics is micro-leakage of root canal fillings which might contribute to the failure of endodontic treatment. To avoid this problem, a variety of sealers have been tested. The objective of this, in vitro, study was to evaluate the shear bond strength of four resin based sealers (AH plus, silver free AH26, RealSeal SE and Perma Evolution permanent root canal filling material) to dentin. Materials and Methods: Forty non-carious extracted lower premolars were used. The 2mm of the occlusal surfaces of teeth were sectioned, to expose the dentin surface. The exposed dentin surfaces of teeth were washed with 5ml of 2.5% NaOCl solution followed by 5ml of 17 % EDTA then rinsed by deionized water to remov

 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data