This study offers the elastic response of the variable thickness functionally graded (FG) by single walled carbon nanotubes reinforced composite (CNTRC) moderately thick cylindrical panels under rotating and transverse mechanical loadings. It’s considered that, three kinds of distributions of carbon nanotubes which are uniaxial aligned in the longitudinal direction and two functionally graded in the transverse direction of the cylindrical panels. Depending on first order shear deformation theory (FSDT), the governing equations can be derived. The partial differential equations are solved by utilizing the technique of finite element method (FEM) with a program has been built by using FORTRAN 95. The results are calculat

The preparation of composite metal oxide to attain high efficiency in removing phenol from wastewater has a great concern. In the present study, the focus would be on adopting antimony-tin oxide coating onto graphite substrates instead of titanium; besides the effect of SbCl3 concentration on the SnO2-Sb2O3 composite would be examined. The performance of this composite electrode as the working electrode in the removal of phenol by sonoelectrochemical oxidation will be studied. The antimony-tin dioxide composite electrode was prepared by cathodic deposition with SnCl2 . 2H2O solution in a mixture of HNO3 and NaNO3, with different concentrations of SbCl3. The SnO2-Sb2O3 deposit layer’s structure and morphology were examined and the 4 g/l Sb

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

Single Point Incremental Forming (SPIF) is a forming technique of sheet material based on layered manufacturing principles. The sheet part is locally deformed through horizontal slices. The moving locus of forming tool (called as toolpath) in these slices constructed to the finished part was performed by the CNC technology. The toolpath was created directly from CAD model of final product. The forming tool is a Ball-end forming tool, which was moved along the toolpath while the edges of sheet material were clamped rigidly on fixture.

This paper presented an investigation study of thinning distribution of a conical shapes carried out by incremental forming and the validation of finite element method to evaluate the limits of the p

The skill scale in most of sport activity monitoring a lot of dynamic behaviours conducted with playing situations that help the excerpt's in sport field to evaluate and put right solutions ,soccer one of games that studies in third stage in college and take skills ,dribbling , passing, shooting these skills helps to execute the plans in game ,the researchers notice that there is no test measure the skills of the game in the beginning of the first semester especially in the method of soccer in physical education college and the problem of the research were by answering the question that is there test connect between one or more that one of skill to measure the ability of students to execute the plans in soccer and the conclusion was the bui

This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg