Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

Iraq suffers from serious pollution with harmful particles that have important direct and indirect effects on human activities and human health. In this research, a system for detecting pollutants in the air was designed and manufactured using infrared laser technology. This system was used to detect the presence of pollutants in the dust storms that swept the city of Baghdad which could have a negative impact on human health and living organisms.

The designed detection system based on the use of infrared laser (IR) with a wavelength of 1064 nm was used for the purposes of detecting pollutants based on the scattering of the laser beam from these pollutants. The system was aligned to obtain the best signal for the scattered rays, w

Background: Waterpipe and cigarette are two products of tobacco consumption, tobacco use has detrimental effects on the oral cavity, numerous studies around the world have reported a significant relationship between smoking and increase dental caries and viable count of cariogenic bacteria, Materials and Methods: unstimulated saliva was collected from 84 subjects and divided equally into three groups waterpipe smokers, cigarette smokers, and non-smokers all of the participants are adult male aged between 25-60 years, dental caries was measured by use DMFT index, while S.mutans and S.sobrinus were isolated by using a selective medium SB 20M (Sugar bacitracin-20 modified) agar Results: this present study showed a significant (p≤0.01)

   In southern Iraq, the Yamama Formation has been a primary carbonate resource since the Lower Cretaceous era. This study covers Siba Field, which is located in southeastern Iraq. This paper will be devoted to a YC unit of study. The most crucial step in reservoir management is petrophysical characterization. The primary goal of this research is to assess the reservoir features and lithology of the Yamama (YC) Formation in the Siba region. Accessible excellent logs include sonic, density, neutron, gamma-ray, SP, and resistivity readings. The Interactive Petrophysics (IP4.4) program examined and estimated petrophysical features such as clay volume, porosity, and water saturation. The optimum approach was the neutron density and clay vo

This work presents a five-period chaotic system called the Duffing system, in which the effect of changing the initial conditions and system parameters d, g and w, on the behavior of the chaotic system, is studied. This work provides a complete analysis of system properties such as time series, attractors, and Fast Fourier Transformation Spectrum (FFT). The system shows periodic behavior when the initial conditions xi and yi equal 0.8 and 0, respectively, then the system becomes quasi-chaotic when the initial conditions xi and yi equal 0 and 0, and when the system parameters d, g and w equal 0.02, 8 and 0.09. Finally, the system exhibits hyperchaotic behavior at the first two conditions, 0 and 0, and the bandwidth of the chaotic

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

The reaction of starting materials (L-asCl2):bis[O,O-2,3;O,O-5,6-(chloro(carboxylic) methylidene)]- -L-ascorbic acid] with glycine gives new product bis[O,O-2,3,O,O-5,6-(N,O-di carboxylic methylidene N-glycine)-L-ascorbic acid] (L-as-gly) which is isolated and characterized by, Mass spectrum UV-visible and Fourier transform infrared spectrophotometer (FT-IR) . The reaction of the (L-as-gly) with M+2; Co(II) Ni(II) Cu(II) and Zn(II) has been characterized by FT- IR , Uv-Visible , electrical conductivity, magnetic susceptibility methods and atomic absorption and molar ratio . The analysis showed that the ligand coordinate with metal ions through mono dentate carboxylic resulting in six-coordinated with Co(II) Ni(II) Cu(II) ions while with

Stimulative effect of 10 mW He-Ne laser on the phagocytic activity of human polymorphonuclear leukocytes( PMNs) has been studied in vitro. Normal polymorphonuclear leucocytes were isolated from the human peripheral blood. A mixture of 0.25 ml of Hanks solution, 0.25 ml of serum, 0.25 ml of Candida albicans suspension and 0.25 ml of PMNs suspension was prepared. The samples of mixture of PMNs and Candida were subdivided in 1 ml ependrof tubes and irradiated to He-Ne laser for 1, 3, 5, 10 and 20 min. The diameter of the irradiated area was 0.8 cm. For calculation of Phagocytic index before and after irradiation, the samples were incubated (37°C) at 5, 15, 30, 60 min. The slides of samples were prepared and stained using Giemsa stain. The

Statisticians often use regression models like parametric, nonparametric, and semi-parametric models to represent economic and social phenomena. These models explain the relationships between different variables in these phenomena. One of the parametric model techniques is conic projection regression. It helps to find the most important slopes for multidimensional data using prior information about the regression's parameters to estimate the most efficient estimator. R algorithms, written in the R language, simplify this complex method. These algorithms are based on quadratic programming, which makes the estimations more accurate.

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and