We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

Background: Bone mineral density (BMD) has been assessed using Dual-Energy X-ray absorptiometry (DEXA). This procedure is considered to be of vital importance in assessing the general condition of individuals concerning their skeletal mineralization. BMD is measured according to the results of the DEXA examination of the vertebral column and pelvis. Although diabetes mellitus (D.M.)is known to affect BMD, the information regarding this relationship is not currently particularly clear. Objective: This study concentrates on the point that the assessment of BMD for the vertebral column is insuffi-cient to give a realistic and correct picture of the mineralization of the remaining part of the skeleton. Besides, this study elicited a gen

Background: Polymethylmethacrylate (PMMA) is the most ‎commonly used m‏aterial in denture construction. This material is ‎far from ideal in fulfilling the‎ mechanical requirements, like low impact and transverse strength and poor thermal conductivity are present in this material. The purpose of this study was to study the effect of addition a composite which include 1%wt silanized silicone dioxide nano fillers (SiO2) and 1wt% oxygen plasma treated polypropylene fiber (PP) on some properties of heat cured acrylic resin denture base material (PMMA). Materials and methods: One hund‏red (100) prepared specimens were divided into five groups according to the tests, each group consisted of 20 specimens and t

In this research, an experimental study was conducted to high light the impact of the exterior shape of a cylindrical body on the forced and free convection heat transfer coefficients when the body is hold in the entrance of an air duct. The impact of changing the body location within the air duct and the air speed are also demonstrated. The cylinders were manufactured with circular, triangular and square sections of copper for its high thermal conductivity with appropriate dimensions, while maintaining the surface area of all shapes to be the same. Each cylinder was heated to a certain temperature and put inside the duct at certain locations. The temperature of the cylinder was then monitored. The heat transfer coefficient were then cal

Pure cadmium oxide films (CdO) and doped with zinc were prepared at different atomic ratios using a pulsed laser deposition technique using an ND-YAG laser from the targets of the pressed powder capsules. X-ray diffraction measurements showed a cubic-shaped of CdO structure. Another phase appeared, especially in high percentages of zinc, corresponding to the hexagonal structure of zinc. The degree of crystallinity, as well as the crystal size, increased with the increase of the zinc ratio for the used targets. The atomic force microscopy measurements showed that increasing the dopant percentage leads to an increase in the size of the nanoparticles, the particle size distribution was irregular and wide, in addition, to increase the surfac

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For

Silver nanoparticles synthesized by different species