Many important archaeological sites in Iraq still need to be preserved. Some of these sites were subjected to destruction and negligence. So, exploring these sites represents a priority for its protection. A 2D Electrical Resistivity Imaging (ERI) as a non-invasive geophysical survey method was implemented at a part of the Borsippa archaeological site near Babylon to search for the subsurface archaeological artefacts/structures. Electrical resistivity measurements were carried out using a Dipole-Dipole array. Steps were taken to process and filter using Horizontal profiles, forward modelling, and 2D inverse models to analyze the resistivity measurements. The ERI inversion results show that the superficial conductive zone produced va

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

With the great development in the field of the Internet, the talk about the new media and its implications began, And its interactive services have made the future of media material sometimes participating in it and manufacturing it at other times,
the public is seeking information and choosing the appropriate ones, as well as exchanging messages with the sender after what the role of the receiver is just receiving information only.
This study aims to demonstrate the effects of using digital media in various forms and types to construct the value system of Iraqi society through the identification of the following aims:
Identify the most popular digital media for the Iraqi public in their daily lives on the Internet.
Identify

Poly methyl methacrylate PMMA polymer could be considered the main material that used mostly in the recent years in denture base fabrication. It commonly known by it is poor strength properties such as low impact strength. The aim of the present research was to enhance the performance of PMMA denture base through the addition of two kind of nanoparticles (nano particles that selected from artificial and natural sources). Nano -particles from both Al2O3 and crushed peanut Peel were used for comparing purposes.Various weight fraction used in this study for both kinds of the additive (1%, 2% and 3%). Moreover, in this work a study and evaluation in impact strength (I.S.) value were done before and after immersion. The new prepared nanocompo

A study was carried out to analysis of some heavy metals in nine different types of vinegar, belong to Grape, Apple, Synthetic White, Date, Hawthorn, Garlic, Cactus, Pomegranate and Ginger vinegar, which are locally available in Iraqi folk medicine markets. The concentrations of heavy metals in the studied samples including, Cr, Mg, Mn, Zn, Fe, Cd, Ni, Pb and Ag, were determining by using flame atomic absorption spectrophotometry. All data were subjected to statistical analysis by calculating accuracy, precision and correlation coefficient for each concentrations level. The results indicate that Ni was recorded the highest concentration in all studied samples except, Ginger and cactus vinegar, each one receded the highest concentration valu

The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.