This research studies the effect of particle packing density on sintering TiO2 microstructure. Sintering experiment was conducted on compacts involving of monodisperse spherical TiO2 particles. The experimental results are modeled using L2-Regression technique in studing the effect of two theoretical values of 55% and 69% of initial packing densities. The mathematical simulation shows that the lower values of density compacts sintered fast to theoretical density and this reflects that particle packing density improved densification rate because of the competing influence of grain growth at higher values of densities.
Abstract:
Most of the studies on this subject, small industrial projects, by researchers and scholars in the economic field show the great and increasing importance of doing this kind of projects, the extent of which can be determined by the contribution of these projects to indicators and macroeconomic and sectorial variables. So this research aims to show the extent of the economic contribution of projects in selected international experiences and in the Iraqi economy. As international experiences have provided the opportunity for the progress and growth of small projects in their economies, which led to an increase in the contribution of these projects in the recruitment of economically active manpower, in added
... Show MoreThis research is devoted to study the effect of different in weight percentage of Sio2 particles and glass fibers (5, 10, 15, 20) wt. % on the wear rate epoxy resin. The results show that the value of hardness increase with the increase for the weight percentage of reinforcing particles and fibers, while the wear rate decrease with the increase the load level of the reinforcing particles and fibers . The largest value of the hardness, and the lowest value of the wear rate for epoxy reinforced with 20% of SiO2, the wear rate increase in general with increasing the applied load.
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
... Show MoreInfrastructure, 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
... Show MoreThis study aimed to improve the microencapsulation technique using a type coating the encapsulation Layer by Layer, which provide the best protection for life Lactobacillus casei in the extrusion method and use the microencapsulation of materials of the protein concentrated by protein 80% and the coating with alginate and chitosan have the results showed the variation in the difference of the binding process encapsulation yield among the types of coating through. by studying of these the effect o stability of the bio probiotic free cell and the three types coated towards three different concentrations from bile salts 0, 0.3, 0.5 and 0.7% when the periods of time different of zero and two and three hours at incubation the recorded
... Show MoreIn this study, dependence of gamma-ray absorption coefficient on the size of Pb particle size ranging from 200µm up to 2.5mm, using different weights of each particle size. The results show that gamma-ray attenuation coefficient is inversely proportional with the size of Pb particle size due to the reduction of the spaces between the lead particles.
Background: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exp
... Show MoreIn an earlier paper, the basic analytical formula for particle-hole nuclear state densities was derived for non-Equidistant Spacing Model (non-ESM) approach. In this paper, an extension of the former equation was made to include pairing. Also a suggestion was made to derive the exact formula for the particle-hole state densities that depends exactly on Fermi energy and nuclear binding energies. The results indicated that the effects of pairing reduce the state density values, with similar dependence in the ESM system but with less strength. The results of the suggested exact formula indicated some modification from earlier non-ESM approximate treatment, on the cost of more calculation time
BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.