The aim of this study is to propose mathematical expressions for estimation of the flexural strength of plain concrete members from ultrasonic pulse velocity (UPV) measurements. More than two hundred
pieces of precast concrete kerb units were subjected to a scheduled test program. The tests were divided into two categories; non-destructive ultrasonic and bending or rupture tests. For each precast unit, direct and indirect (surface) ultrasonic pulses were subjected to the concrete media to measure their travel velocities. The results of the tests were mointered in two graphs so that two mathematical relationships can be drawn. Direct pulse velocity versus the flexural strength was given in the first relationship while the second equati

This research of using Feldspar in the production self compacting concrete (SCC) ( 5,10,15 )% as partial replacement by weight of cement .In this research some of fresh properties of SCC ( slump flow used V-funnel test and filling ability used ( U- box test ) for concrete mixes and also some of the harden properties of SCC ( compressive and flexural tests ). The research results showed that negative effect of Feldspar on the fresh properties of self compacting concrete but the positive effect of Feldspar on the harden properties of self compacting concrete .

This research studies the influence of water source on the compressive strength of high strength concrete. Four types of water source were adopted in both mixing and curing process these are river, tap, well and drainage water (all from Iraq-Diyala governorate). Chemical analysis was carried out for all types of the used water including (pH, total dissolved solids (TDS), Turbidity, chloride, total suspended solid (TSS), and sulfates). Depending on the chemical analysis results, it was found that for all adopted sources the chemical compositions was within the ASTM C 1602/C 1602M-04 limits and can be satisfactorily used in concrete mixtures. Mixture of high strength concrete for compressive strength of (60 MPa) was designed and checked using

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

     The open hole well log data (Resistivity, Sonic, and Gamma Ray) of well X in Euphrates subzone within the Mesopotamian basin are applied to detect the total organic carbon (TOC) of Zubair Formation in the south part of Iraq. The mathematical interpretation of the logs parameters helped in detecting the TOC and source rock productivity. As well, the quantitative interpretation of the logs data leads to assigning to the organic content and source rock intervals identification. The reactions of logs in relation to the increasing of TOC can be detected through logs parameters. By this way, the TOC can be predicted with an increase in gamma-ray, sonic, neutron, and resistivity, as well as a decrease in the density log

Background: In Iraqi communities, the workers considered the largest population groups, so increasing their dental education by increasing the care for their dental health knowledge and behavior is very important, the present study was aimed to evaluate the gingival health and oral hygiene in relation to knowledge and behavior among a group of a workers selected randomly from Al Fedaa company in Baghdad city. Materials and methods: A sample of 110 workers (65 men and 45 women) included in this study, a questionnaire used to evaluate their oral health knowledge and behavior. The gingival health condition of the workers was examined by using Loe and Silness index (1963), Silness and Loe index (1964) was used to asses plaque quantity, and Ramf

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and