Background: To investigate the effect of different types of storage media on enamel surface microstructure of avulsed teeth by using atomic force microscope.Materials and methods : Twelve teeth blocks from freshly extracted premolars for orthodontic treatment were selected . The study samples were divided into three groups according to type of storage media :A-egg white , B- probiotic yogurt , and C-bovine milk . All the samples were examined for changes in surface roughness and surface granularity distribution  using atomic force microscope, at two periods: baseline, and after 8 hours of immersing in the three types of storage media. Results: Milk group had showed a significant increase in the mean of the  roughness values at

The choice of binary Pseudonoise (PN) sequences with specific properties, having long period high complexity, randomness, minimum cross and auto- correlation which are essential for some communication systems. In this research a nonlinear PN generator is introduced . It consists of a combination of basic components like Linear Feedback Shift Register (LFSR), ?-element which is a type of RxR crossbar switches. The period and complexity of a sequence which are generated by the proposed generator are computed and the randomness properties of these sequences are measured by well-known randomness tests.

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

BackgroundThe diagnosis and important aspects in treating acute abdomen during pregnancy tend to be delayed due to the peculiar physiological features of pregnancy and the restrictions imposed on imaging diagnostic techniques such as x-ray and CT.Aim of the studyTo identify the most common causes of acute abdomen during pregnancy and identifying the approaches for early diagnosis and to take a correct decision for surgery and assigning the complications that may occur during and/or after surgery for the mother and the fetus.Patients and Methods This is a prospective study that involves data obtained from 91 pregnant patients admitted in the surgical wards in Baghdad teaching hospital during the period from January 2008 to December 2009 .

Abstract

The current study aims to identify the resilience of university students, as well as identify the differences in resilience according to the variable of gender and specialization. The research sample consisted of (382) students studying at Baghdad University. To measure Resilience, a questionnaire of (48) items was designed to collect the needed data. The results showed that the students of the University of Baghdad possess resilience. There are no differences in resilience according to gender and specialization.

Maximum values of one particle radial electronic density distribution has been calculated by using Hartree-Fock (HF)wave function with data published by[A. Sarsa et al. Atomic Data and Nuclear Data Tables 88 (2004) 163–202] for K and L shells for some Be-like ions. The Results confirm that there is a linear behavior restricted the increasing of maximum points of one particle radial electronic density distribution for K and L shells throughout some Be-like ions. This linear behavior can be described by using the nth term formula of arithmetic sequence, that can be used to calculate the maximum radial electronic density distribution for any ion within Be like ions for Z<20.

     In this paper, some estimators for the unknown shape parameter and reliability function of Basic Gompertz distribution have been obtained, such as Maximum likelihood estimator and Bayesian estimators under Precautionary loss function using Gamma prior and Jefferys prior. Monte-Carlo simulation is conducted to compare mean squared errors (MSE) for all these estimators for the shape parameter and integrated mean squared error (IMSE's) for comparing the performance of the Reliability estimators. Finally, the discussion is provided to illustrate the results that summarized in tables.