This paper describes the geotechnical properties of Al-Ammarah soil of Ammarah city in Messan Governorate-southern parts of Iraq. Data and other information taken from numbers of geotechnical reports that performed under the supervision of Consulting Engineering Bureau of Baghdad University. This research is devoted to study the correlation between different physical properties such as (LL, PI, LI, n,t, e) with different mechanical properties such as (qu, cc, cs, SPT). The correlation is verified using simple regression analysis. From the regression results it was found that there is direct correlation between different parameters. By using the correlation-with some information- preliminary investigation stages and studies of any s

This paper describes the geotechnical properties of Al-Ammarah soil of Ammarah city in Messan Governorate-southern parts of Iraq. Data and other information taken from numbers of geotechnical reports that performed under the supervision of Consulting Engineering Bureau of Baghdad University. This research is devoted to study the correlation between different physical properties such as (LL, PI, LI, n,t, e) with different mechanical properties such as (qu, cc, cs, SPT). The correlation is verified using simple regression analysis. From the regression results it was found that there is direct correlation between different parameters. By using the correlation-with some information- preliminary investigation stages and studies of any s

Background: Gastroesophageal reflux disease, is a quite prevalent gastrointestinal disease, among which gastric content (excluding the air) returns into the oral cavity. Many 0ral manifestations related t0 this disease include tooth wear, dental caries also changes in salivary flow rate and pH. This study was conducted among gastroesophageal reflux disease patients in order to assess tooth wear in relation to salivary flow rate and pH among these patients and the effect of gastroesophageal reflux disease duration on this relation. Materials and methods: One hundred patients participate in this cross-sectional study for both genders and having an age range of 20-40 years old, patients had been endoscopically identified as having gastroeso

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

The present work included study of the effects of weather conditions such as solar radiation and  ambient temperature on solar panels (monocrystalline 30 Watts) via proposed mathematical model, MATLAB_Simulation was used by scripts file to create a special code to solve the mathematical model , The latter is single –diode model (Five parameter) ,Where the effect of ambient temperature and solar radiation on the output of the solar panel was studied, the Newton Raphson method was used to find the  output current of the solar panel and plot P-V ,I-V curves, the performance of the PV was determined at Standard Test Condition (STC) (1000W/m2)and a comparison between theoretical and experimental results were done .The best efficiency

DBN Rashid, 2012 - Cited by 2