Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

Objective: To evaluate the effect of mouth rinses (Biofresh and ZAK) on the surface micro hardness
of two light cure restorative material (Tetric ceram ivoclar-vivadent) and (3M Z 250) dental
composite.
Methodology: The microhardness values of (sixty) composite specimens were measured at the top
surfaces after 24 hours of immersion in different solutions (Biofresh, Zak mouth wash and distilled
water as control). Comparison done using descriptive statistics (mean, SD, SEM, minimum and
maximum values) and inferential statistics (ANOVA and LSD) test.
Results: The biofresh mouth rinse which has high alcohol containing has less effect on
microhardness of tetric ceram than the zak &distiled water , while the effect

Background: Nanotechnology represents a new science that promises to provide a broad range of uses and improved technologies for biological and biomedical applications. One of the reasons behind the intense interest is that nanotechnology permits synthesis of materials that have structure is less than 100 nanometers. The present work revealed the effect of zinc oxide nanoparticles (ZnO NPs) on Streptococcus mutans of Human Saliva in comparison to de-ionized water. Materials and methods: Streptococcus mutans were isolated from saliva of forty eight volunteers of both sexes their age range between 18-22 years and then purified and diagnosed according to morphological characteristic and biochemical tests. Different concentrations of ZnO NPs w

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Incorporation of chemical additives has long been a technique used to improve properties of the gypsum products. The purpose of this work was to study the effects of adding a combination of gum Arabic and calcium hydroxide to a type III dental stone and type IV improved die stone with different proportion. The effect on water/powder ratio, and surface hardness was determined. Material and method: Both material stone and die stone were blended with two proportion of additives so that each material was mixed twice but with different proportion of gum Arabic (0.1% and 0.2%) and calcium hydroxide (0.5 % and 0.3%). Data for hardness were subjected to two-way analysis of variance. Results: The results revealed that the chemical additi