Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

Abstract Planetary nebulae (PN) represents the short phase in the life of stars with masses (0.89-7) M☉. Several physical processes taking place during the red giant phase of low and intermediates-mass stars. These processes include :1) The regular (early ) wind and the envelope ejection, 2) The thermal pulses during Asymptotic Giant Branch (AGB ) phase. In this paper it is briefly discussed how such processes affect the mass range of Planetary Nebulae(PN) nuclei(core) and their evolution, and the PN life time, and fading time for the masses which adopted. The Synthetic model is adopted. The envelope mass of star (MeN ) and transition time (ttr) calculated respectively for the parameter (MeR =1.5,2, 3×10-3 M☉). Another time scale is o

Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

High temperature superconductor with nominal composition Bi1.6Pb0.4Sr1.8Ba0.2Ca2 Cu3O10+? was prepared by solid state reaction method. Two sets of samples have been prepared .The first one was quenched in air; the second set was quenched in liquid nitrogen. X-ray diffraction analyses showed an orthorhombic structure with two phases, high –Tc phase (2223) and low-Tc phase (2212) in addition to that impure phase was found. It has been observed that quenched in air samples display a sharp superconducting transition and a higher-Tc phase than that of the quenched in liquid nitrogen samples.

Maintenance of machine tools can be improved significantly by analyzing the operating of manufacturing process with the real-time monitoring system for 3-D single point deformation measurements. Therefore, the process of manufacturing could be optimized with less cost. Recently, wireless technology and internet of things (IOT) applied on intelligent machine has witnessed a significant advance with augmented virtuality, the analysis and the process certainly would contribute to enhance the intelligence of that machine. This paper presents a group of the wireless sensors and 3D animation technologies for data monitoring and analyzing. Three degree of freedom robotic hand structure has been selected as a prototype to be form the process of the