It is suitable to use precast steel-concrete composite beams to quickly assemble a bridge or a building, particularly in isolated regions where cast-in-situ concrete is not a practical option. If steel-concrete composite beams are designed to allow demountability, they can also be extremely useful in the aftermath of natural disasters, such as earthquakes or flooding, to replace damaged infrastructure. Furthermore, rapid replacement of slabs is extremely beneficial in case of severe deterioration due to long-term stressors such as fatigue or corrosion. The only way to rapidly assemble and disassemble a steel-concrete composite structure is to use demountable shear connectors to connect/disconnect the steel beams to/from the concrete slab. I

Background: Errors of horizontal condylar inclinations and Bennett angles had largely affected the articulation of teeth and the pathways of cusps. The aim of this study was to estimate and compare between the horizontal condylar (protrusive) angles and Bennett angles of full mouth rehabilitation patients using two different articulator systems. Materials and Methods: Protrusive angles and Bennett angles of 50 adult males and females Iraqi TMD-free full mouth rehabilitation patients were estimated by using two different articulator systems. Arbitrary hinge axis location followed by protrusive angles and Bennett angles, estimation was done by a semiadjustable articulator system. A fully adjustable articulator system was utilized to locate th

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte