This study aims to analyze spectra in real-time for λ Draconids, σ Hydrids, μ Virginid, and one sporadic meteor using spectroscopic chemical analysis and diagnose plasma parameters. Good-resolution spectroscopy and a CCD camera for meteor observation were used concurrently to examine the ablation spectra of these meteorites in situ. The Boltzmann and Lorentz methods were then used to determine the temperature and density of electrons, the length of Debye, and the frequency of plasma. Furthermore, spectra data can be analyzed and compared to data from other sources. Spectrum tests can be utilized to identify the chemical structure of meteorites' plasma.

Empirical equation has been presented to predict the optimum hydrodynamic
pressure gradient with optimum mud flow rate (one equation) of five Iraqi oil wells
to obtain the optimum carrying capacity of the drilling fluid ( optimum transport
cuttings from the hole to the surface through the annulus).
This equation is a function of mud flow rate, mud density and penetration
rate without using any charts or graphs.
The correlation coefficient accuracy is more than 0.9999.

This paper describes a number of new interleaving strategies based on the golden section. The new interleavers are called golden relative prime interleavers, golden interleavers, and dithered golden interleavers. The latter two approaches involve sorting a real-valued vector derived from the golden section. Random and so-called “spread” interleavers are also considered. Turbo-code performance results are presented and compared for the various interleaving strategies. Of the interleavers considered, the dithered golden interleaver typically provides the best performance, especially for low code rates and large block sizes. The golden relative prime interleaver is shown to work surprisingly well for high puncture rates. These interleav

Maximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.

The interest of this paper is that

Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

Loratadine is a long acting non-sedating anti-histaminic agent that was developed for the treatment of seasonal allergic rhinitis, whose anti-histaminic action is more effective than the other anti-histaminic drugs available commercially. This project was carried out to prepare an acceptable suspension through studying the release of drug in presence of different types and concentrations of suspending agents such as polysorbate 40, xanthan gum, sodium carboxymethylcellulose (NaCMC), aluminum magnesium silicate (veegum) and sodium alginate. The effects of these suspending agents were studied at pH 1.2 (0.1N HCl) and 37 Ù’C. The results showed that the release rate of loratadine in the presence of these suspending agents was dependent o

Chemical pesticides have an impact on other living organisms in addition to their intended target organisms. Any chemical pesticide is therefore made safe for use by examining its biological characteristics and side effects. The present study was aimed at determining the resistance efficiency of six bacterial isolates obtained from malathion-contaminated soils. Bacteria were isolated from soil samples collected in Adhamiya, Baghdad, Iraq. Biochemical tests and VITEK 2 compact equipment were used to identify the bacterial isolates. Primary and secondary screening tests were conducted on the bacterial isolates for resistance against malathion pesticides. The optimal bacterial growth conditions were determined in malathion-contaminated media.