This study focuses on evaluating the suitability of three interpolation methods in terms of their accuracy at climate data for some provinces of south of Iraq. Two data sets of maximum and minimum temperature in February 2008 from nine meteorological stations located in the south of Iraq using three interpolation methods. ArcGIS is used to produce the spatially distributed temperature data by using IDW, ordinary kriging, and spline. Four statistical methods are applied to analyze the results obtained from three interpolation methods. These methods are RMSE, RMSE as a percentage of the mean, Model efficiency (E) and Bias, which showed that the ordinary krigingis the best for this data from other methods by the results that have b

Background: With the increased in the demands of adult orthodontics, the challenge of direct bonding to non-enamel surface (zirconium) had been increased. The present study was carried out to compare the shear bond strength of three different brackets (stainless steel, sapphire and composite) bonded to zirconium surface and study the mode of bond failure. Materials and methods: The sample was comprised of 30 models (8mm *6mm*1.5mm) of full contour zirconium veneers. They were divided into three groups according to the brackets type; all samples were treated first by sandblast with aluminum oxide particle 50 µm then coated by z-prime plus primer. A central incisor bracket of each group was bonded to the prepared zirconium surface with lig

The present study was carried out to compare the physicochemical characteristics of eggs of guinea fowl, turkeys and domestic chickens outdoor reared in traditional farms in Baghdad, Iraq. A total of 166 fresh eggs; 32 eggs from guinea fowls (Numida meleagris), 44 eggs from turkeys (Meleagris gallopavo) and 90 eggs from domestic chickens; were collected. Egg weight, percentage of egg components, chemical composition (protein, lipids, and ash), and lipid profile were determined. Results revealed the significant differences in egg weight among studied birds. The average egg weights for guinea fowl, turkey, and indigenous chicken were 48.51 ± 0.72, 52.15 ± 0.74 and 61.24 ± 0.22 g, respectively. No significant differences were found in egg c

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as