ENGLISH

RESRAD is a computer model designed to estimate risks and radiation doses from residual radioactive materials in soil. Thirty seven soil samples were collected from the area around the berms of Al-Tuwaitha site and two samples as background taken from an area about 3 km north of the site. The samples were measured by gamma-ray spectrometry system using high purity germanium (HPGe) detector. The results of samples measurements showed that three contaminated area with 238U and 235U found in the study area. Two scenarios were applied for each contaminated area to estimate the dose using RESRAD (onsite) version 7.0 code. The total dose of resident farmer scenario for area A, B and C are 0.854, 0.033 and 2.15×10-3 mSv.yr-1, respectively. Whi

The persons who Allah Ioves them in the holly Quran

Objectivity Study0Dr 0muyad Turky Ali 

Allah men tioned in Auran the loving of benevolent and who Allah loves him gave him everything 0the loving of benevolent came fist and after that the loving of justice who remove injustice and after that loving purified and in noeent 0After that mentioning loving of Knighters ( fighters )The eharity with money and to clear up the justice and loving purified is a reason of accessing paradise 0 

Oral squamous cell carcinoma (OSCC) is the most common malignant neoplasm of the oral mucosa. Human papillomavirus (HPV) virus cause a broad scope of diseases from benign to invasive tumors, types 16 and 18 classified as carcinogenic to humans. This study aimed to provide the first molecular characterization of HPV types in Iraq. Thirty-five unstimulated whole saliva samples were collected from histopathologically confirmed patients with oral cancer were enrolled in this study. Genomic DNA was extracted from exfoliating cells to amplify HPV-DNA using HPV-L1 gene sequence primers by polymerase chain reaction method (PCR), the viral genotyping was performed using direct sequencing method. HPV genotypes identified were deposited in Gen

Oral squamous cell carcinoma (OSCC) is the most common malignant neoplasm of the oral mucosa. Human papillomavirus (HPV) virus cause a broad scope of diseases from benign to invasive tumors, types 16 and 18 classified as carcinogenic to humans. This study aimed to provide the first molecular characterization of HPV types in Iraq. Thirty-five unstimulated whole saliva samples were collected from histopathologically confirmed patients with oral cancer were enrolled in this study. Genomic DNA was extracted from exfoliating cells to amplify HPV-DNA using HPV-L1 gene sequence primers by polymerase chain reaction method (PCR), the viral genotyping was performed using direct sequencing method. HPV genotypes identified were deposited in Gen

Importance of the research:
The importance of any educational or scientific research through its intellectual arena of facts supply the individual and society, Supports Knowledge and Science Group, which raised will be locked in these topics in the future.
This research seeks to shed light on the image and the role of women and men in the books of the Arabic language in primary education (primary), To illustrate the negative effects of the phenomenon of sexism in textbooks, And its negative impact on emerging, And stay away as much as possible about the distinction between the sexes in the roles and qualities in textbooks traditional stereotypes and remove that put both sexes templates hinder the development of the individual and t

In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le