Adsorption is a simplified new way, easy application , economical and environmentally friendly. In which the use of certain types of plants to remove or reduce toxic heavy metals from water. The current study involved the use of a non-living biomass as a powder for local plant available in the Iraqi environment is Phragmites australis .This the study showed the high ability of this plant to remove cadmium and lead ions from the aqueous solutions within variable experimental factors by column bed method which were used to test different sizes of plant powder were (500.1000, 1500 and 2000) μm . These sizes treated with initial concentration of Cd(II), Pb(II) was 25ppm , separately To test the optimum size for maximum adsorption and was 1000 μm . After that were tested different concentrations of Cd, Pb are (25, 50, 75, 100, 125,150,175,200)ppm with powder size of 1000 μm . And the optimum concentration was 100ppm. Different flow rates (0.5, 1, 1.5, 2) ml / min were tested with the powder size at 1000 μm and concentration for each metal was 100ppm and the optimum flow rate was 1 ml / min . All the experiments conducted at constant the mean of pH was 5, 32, temperature 22 ± 2 , contact time ranged (22-40) minutes. Results of statistical analysis showed that the optimum conditions of the maximum adsorption were at 1000 μm of powder size, 100ppm of initial metal concentration, flow rate of 1 ml / min and the high removal rates of cadmium and lead ions by P. australis were 95,16 % and 92.76% , respectively .
The adsorption of Cadmium and Lead Ions from aqueous solutions using non living biomass of Phragmites australis
Cadmium and Lead
Phragmites australis
Adsorption
Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
Exponentiated Weibull Distribution (EWD)
Reliability of multi-component Stress – Strength models R(s
k)
Maximum likelihood estimator (MLE)
Moment estimator (MOM)
shrinkage method (Sh)
Least Squares Estimator (LS)
Rank Set Sampling (RSS). and mean squared error (MSE).
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
Today the trend is to perform software development work via distributed geographical area among team
individual or even as an organization. However
due to the global market and international presence of many companies
there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space
time and organizational boundaries via information and communication technologies. A global virtual team relies on communication
collaboration
and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study
we investigated factors that affect global virtual teams’ performance
factors considered include cultural differences
language problems
time-zone differences
team size
technical problems
lack of trust
lack of sufficient training
and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand
team size is the lowest level of effect on global virtual teams’ performance. © 2005 - 2016 JATIT & LLS. All rights reserved.
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