Nonlinear regression models are important tools for solving optimization problems. As traditional techniques would fail to reach satisfactory solutions for the parameter estimation problem.  Hence, in this paper, the BAT algorithm  to estimate the parameters of  Nonlinear Regression models is used . The simulation study is considered to investigate the performance of the proposed algorithm with the maximum likelihood (MLE) and Least square (LS) methods. The results show that the Bat algorithm provides accurate estimation and it is satisfactory for the parameter estimation of the nonlinear regression models than MLE and LS methods depend on Mean Square error.

Polycyclic aromatic hydrocarbons (PAHs) were measured in aerosol from air samples, which collected for the period from April 2012 to February 2013, in Baghdad city, at Daura Refinery. Aerosol samples were collected on cellulose fiber filters for 1.5 h in each site for the morning and evening time. These aerosol samples undergone soxhlet extraction.
After the extraction, 49 samples were analyzed by GC-MS in order to determin 16 PAH compounds. The parameters temperature, relative humidity and wind speed were measured during the measurement period. The PAH concentrations were different for location inside and outside Daura refinery. Naphthalene was the most abundant PAH detected in all points at the site sampling for all seasons. There i

In this work, an estimation of the key rate of measurement-device-independent quantum key distribution (MDI-QKD) protocol in free space was performed. The examined free space links included satellite-earth downlink, uplink and intersatellite link. Various attenuation effects were considered such as diffraction, atmosphere, turbulence and the efficiency of the detection system. Two cases were tested: asymptotic case with infinite number of decoy states and one-decoy state case. The estimated key rate showed the possibility of applying MDI-QKD in earth-satellite and intersatellite links, offering longer single link distance to be covered.

       In this study, the surface of the epoxy/Al composite is treated using a dielectric barrier discharge (DBD) plasma in the presence of air. The epoxy composite was prepared by mixing 0.1g and 0.3 g aluminum powder with epoxy resin and its hardener in a ratio of 3:1. The surface epoxy/Al composite as a dielectric barrier layer (DB) is studied at an applied frequency of 8 kHz and at three exposure times 0, 2, and 4 min. The UV degradation process has been studied using UV-Visible spectroscopy, for these polymers. The absorbance intensity in the UV region (200–320 nm) was high. The absorbance level decreased after 2 minutes and increased after 4 min exposure time. Before exposure to plasma, the epoxy/Al composite at 0.1 g Al ha

            Semi-parametric regression models have been studied in a variety of applications and scientific fields due to their high flexibility in dealing with data that has problems, as they are characterized by the ease of interpretation of the parameter part while retaining the flexibility of the non-parametric part. The response variable or explanatory variables can have outliers, and the OLS approach have the sensitivity to outliers. To address this issue, robust (resistance) methods were used, which are less sensitive in the presence of outlier values in the data. This study aims to estimate the partial regression model using the robust estimation method with the wavel

In this paper the effect of nonthermal atmospheric argon plasma on the optical properties of the cadmium oxide CdO thin films prepared by chemical spray pyrolysis was studied. The prepared films were exposed to different time intervals (0, 5, 10, 15, 20) min. For every sample, the transmittance, Absorbance, absorption coefficient, energy gap, extinction coefficient and dielectric constant were studied. It is found that the transmittance and the energy gap increased with exposure time, and absorption. Absorption coefficient, extinction coefficient, dielectric constant decreased with time of exposure to the argon plasma

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

     In this research, a type of gram negative bacteria was exposed to non-thermal plasma at a distance of (2 and 3 cm) from the plasma flow nozzle, with the use of an alternating power supply (5KHz), where exposure was made at two different voltages (4.9 and 8 kV). A negative gram of Pseudomonas aeruginosa bacteria was isolated and exposed to non-thermal plasma at different flow rates of argon gas whose value ranged from (1-5) liters/minute. The results showed that bacterial killing rate is directly proportional to distance while exposing the samples to non-thermal plasma, and the best factors by which a complete killing rate was obtained were at a distance of 2 cm with a voltage of 8 kV and a gas flow rate of 5 liters/min,