This study was carried out to study effect of magnetic water ( M0 and M) and different concentrations of coconut extract in Fragaria x ananassa (Duch) C.V Festival. The results showed significant differences in the plants treated with magnetic water ( 0.12 Tesla) and different concentrations of coconut extract C1 (0%), C2 (2.5%), C3 (5%), C4 (7.5%) and C5 (10%) in vegetative parameters as in leaf area and chlorophyll in treatment M0C3 was (53.72 Dcm2, 50.00), respectively, highest leaf number and plant dry weight in MC4 (12.77,14.22 gm), respectively. Results recorded significant differences in fruit parameters such as weight in MC1 (18.97 gm). The maximum fruit number was in MC3 (110), the greatest fruit size was in MC4 (15.78 cm3) and the

Silver Indium Aluminum Selenium AgIn1xAlxSe2 AIAS for x=01 thin films was deposited by thermal evaporation at RT and different︣︢︡ ︠︣1thickness 100 150 and 200 nm on the glass Substrate and p2Si wafer to produce AIAS/p3Si heterojunctionsolarcell4 Structural optical electrical and photovoltaicproperties6 are investigated for the samples XRD analysis reveals that all the deposited AIAS films show polycrystalline structure without any change due to increase of thickness Average diameter and roughness calculated from AFM images shows an increase in its value with increasing thickness The optical absorbance and transmittance for samples are measured using a spectrometer type UV Visible 1800 spectra1photometer to study the energy6gap The

An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the average drag estimated on

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the avera

Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ