In this paper an estimator of reliability function for the pareto dist. Of the first kind has been derived and then a simulation approach by Monte-Calro method was made to compare the Bayers estimator of reliability function and the maximum likelihood estimator for this function. It has been found that the Bayes. estimator was better than maximum likelihood estimator for all sample sizes using Integral mean square error(IMSE).

Some microorganisms can produce nanocellulose, which is known as bacterial nanocellulose (BNC); the most active bacterial producer is acetic acid bacteria (AAB), which is a gram-negative, motile and obligate aerobic belongs to the family Acetobacteraceae. Bacterial nanocellulose has excellent attention in medical (surgical domain), industrial and pharmaceutical fields because of its flexible properties, characteristics and advantages. So, in this study, the AAB (5AC) isolate was isolated from apple vinegar. The production of BNC was performed by using a natural medium called palm dates liquid medium, the produced bacterial Cellulose was purified by using the sodium hydroxide method; it was observed that the wet weight of the BNC was a

Lithium doped Nickel-Zinc ferrite material with chemical formula Ni0.9−2x Zn0.1LixFe2+xO4, where x is the ratio of lithium ions Li+ (x = 0, 0.01, 0.02, 0.03 and 0.04) prepared by using sol-gel auto combustion technique. X-ray diffraction results showed that the material have pure cubic spinal structure with space group Fd-3m. The experimental values of the lattice constant (aexp) were decreased from 8.39 to 8.35 nm with doped Li ions. It was found that the decreasing of the crystallite size with addition of lithium ions concentration. The radius of tetrahedral (rtet) and octahedral (roct) site were computed from cation distribution. SEM images have been taken to show the morphology of compound. The dielectric parameters [dissipation fa

The aim of this paper is to estimate a nonlinear regression function of the Export of the crude oil Saudi (in Million Barrels) as a function of the number of discovered fields.

 Through studying the behavior of the data we show that its behavior was not followed a linear pattern or can put it in a known form so far there was no possibility to see a general trend resulting from such exports.

We use different nonlinear estimators to estimate a regression function, Local linear estimator, Semi-parametric as well as an artificial neural network estimator (ANN).

The results proved that the (ANN) estimator is the best nonlinear estimator am

Recent research has examined the improvement of physical and dielectric properties of BaTiO₃ ceramic material by small addition of excess TiO₂ or BaCO₃. The prepared samples sintered at different temperatures and varying soaking time. The results show that increasing the sintering temperature within 1350°C and soaking time of 10 hrs give better electrical and physical properties, which indicate the reaction is complete at higher temperature and period.

A study carried out on ceramic material made at (a-Al₂O₃) doped with MgO (0.5 , 0.3 , 0.2,0.1)%,with particle size at 63mm.
A Hydraulic press of 5kn at diameter of 2cm.A nnalelling at 1500C^o and 6 hrs still to see the effect on the changes of the dielectric material. With frequency range at (1K – 1M) Hz. And the result show that at percentage of 0.5% of MgO, the real dielectric material decreased with the increased frequency

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials

In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes