In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Background: Impacted teeth are frequent problem and one of the most affected teeth is the maxillary canine. The early diagnosis of impacted canines by radiographic evaluation is imperative. The aim of this study was to determine the prevalence of impacted maxillary canines in patients attending the Oral diagnosis and Radiology clinic in College of Dentistry, University of Al-Basrah. Materials and Methods: 1280 patients attending the Oral Diagnosis and Radiology clinic in College of Dentistry University of Al-Basrah, between October 2013 and March 2015 were examined for the study. The age of the patients ranged from 15 to 55 years, with a mean age of 22.2 years. Results: The prevalence for maxillary impacted canines in all the cases was fo

The nuclear level density parameter  in non Equi-Spacing Model (NON-ESM), Equi-Spacing Model (ESM) and the Backshifted Energy Dependent Fermi Gas model (BSEDFG) was determined for 106 nuclei; the results are tabulated and compared with the experimental works. It was found that there are no recognizable differences between our results and the experimental -values. The calculated level density parameters have been used in computing the state density as a function of the excitation energies for ⁵⁸Fe and ²⁴⁶Cm nuclei. The results are in a good agreement with the experimental results from earlier published work.

In this study, the results of the uranium concentrations and specific activity in 10 rice samples are described using a solid-state track detector (CR-39). Samples were collected from various local Iraqi markets with different origins (Iraq, India, America, and Thailand). Our findings found that the results of uranium concentration in all studied samples are ranging from (0.55 ± 0.28 to 1.74 ± 0.31) ppm with a weighted average of (1.24 ± 0.99) ppm. Also, results demonstrate that the specific activity values of the studied samples swing between values of (6.88 ± 3.52 and 21.49 ± 3.85) Bq/Kg. The obtained results of the studied rice samples are indicated that it is less than the acceptable limit of those studies established by ma

Charge multipole Coulomb scattering form factors in ⁴⁸Ca nucleus have been reproduced utilizing the theory of nuclear shell. The efficient two-body nuclear potential fpbm is considered to construct the-spin orbit term LS vectors with Harmonic Oscillator HO potential as a wave function of single particle in Fp shell. Discarded spaces ( core + higher configuration) are taken into account through the Core polarization effect by model space with accurate two-body potential of Gogny to  interact the LS operating particles with the discarded space pair ( particle-hole) with energy of excitation equal to 2ћω. Gogny interaction has been selected as it had succeeded in nuclear shell theory. The computed results were compared with th

A numerical study has been carried out to investigate heat transfer by natural convection and radiation under the effect of magnetohydrodynamic (MHD) for steady state axisymmetric twodimensional laminar flow in a vertical cylindrical channel filled with saturated porous media. Heat is generated uniformly along the center of the channel with its vertical surface remain with cooled constant wall temperature and insulated horizontal top and bottom surfaces. The governing equations which used are continuity, momentum and energy equations which are transformed to dimensionless equations. The finite difference approach is used to obtain all the computational results using the MATLAB-7 programming. The parameters affected on the system are Rayl

Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

The levels of lead (pb), copper (cu), cobalt (co) and cadmium (cd) were determined in different kinds of milk and the health risks were evaluated. The mean levels were 0.73±0.21, 0.06±0.01, 0.12±0.01 and 0.14±0.01 ppm for these metals respectively. The levels of pb and cu were found to be insignificant differences (p<0.05), whereas the levels of co and cd, were no significant differences (p>0.05). The dry and liquid kinds of milk were different significantly (p<0.05), whereas the original, was no significant differences (p>0.05). The values for all metals were more than one. The metals pb and cd were detected at highest concentrations in most dry and liquid milk samples.