The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

In this work, two different laser dye solutions were used to host highly-pure silicon nitride nanoparticles as scattering centers to fabricate random gain media. The laser dye was dissolved in three different solvents (ethanol, methanol and acetone) and the final results were obtained for methanol only. The silicon nitride nanoparticles were synthesized by dc reactive magnetron sputtering technique with average particle size of 35 nm. The random gain medium was made as a solid rod with high spectral efficiency and low production cost. Optical emission with narrow linewidth was detected at 532-534 nm as 9 mg of silicon nitride nanoparticles were added to the 10 -5 M dye solution. The FWHM of 0.3 and 3.52 nm was determined for Rhodamine B and

The effects of using aqueous nanofluids containing covalently functionalized graphene nanoplatelets with triethanolamine (TEA-GNPs) as novel working fluids on the thermal performance of a flat-plate solar collector (FPSC) have been investigated. Water-based nanofluids with weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1% of TEA-GNPs with specific surface areas of 300, 500, and 750 m2/g were prepared. An experimental setup was designed and built and a simulation program using MATLAB was developed. Experimental tests were performed using inlet fluid temperatures of 30, 40, and 50 °C; flow rates of 0.6, 1.0, and 1.4 kg/min; and heat flux intensities of 600, 800, and 1000 W/m2. The FPSC’s efficiency increased as the flow rate and hea

Nanotechnology is a continually expanding field for its uses and applications in multiple areas i.e. medicine, science, and engineering. Biosynthesis is straightforward, less-toxicity, and cost-effective technology. TiO2 NPs biosynthesis has attained consideration in recent decades. In this study, probiotic bacteria were isolated from cow’s raw milk samples, and then were identified by using the Vitek2 system; as Leuconostoc spp. included Leuconostoc mesenteroides subsp. mesenteroides (Leu.1), Leuconostoc mesenteroides subsp. cremoris (Leu.4), and Leuconostoc pseudomesenteroides (Leu.14). All Leuconostoc spp. isolates showed an ability for TiO2 NPs bio-production, after being incubated at anaerobic conditions (30 o C/ 24 h) in DeM