This study was conducted to determine the activity of plant Sesbania rostrata and two isolate from arbuscular mycorrhizae fungi (A,B) as a bioremediation of soil polluted by cadmium and lead elements in north and south of Baghdad city. The results showed that the average of soil pollution by cadmium and lead elements in north of Baghdad was less than the average of soil pollution in the south of Baghdad which recorded 10.0, 9.0 mg/kg and 27.0, 25.0 mg/kg respectively. The plant Sesbania recorded ability to accumulate the lead element in shoot system 19.65 mg/kg and in root system 27.2 mg/kg and for cadmium element 19.6, 24.6 mg/kg in shoot and root respectively. The results showed that the isolate A from soil pollution is more effected

An experiment was carried out in a field in Husayniyah sub-district of the Holy Karbala Governorate. The research included studying the impact of the plowing depth and soil moisture on some technical indicators when using the disc plow. The 80 hp New Holland tractor was used in this experiment. Two factors were studied, the first factor is the soil moisture (12- 9%), (16-13%) and (20-17%) and the second factor was the depth of tillage (10-13) cm, (15-18) cm and (20-23) cm, which represented the secondary blocks. Bulk density, percentage of slippage and drawing force were studied. The field trials was conducted according to Split blocks in a randomized complete block design in three replicate. Consequences showed (according to the conditions

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th

Abstract

In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controll