Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % we

The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % were

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

In this work, the precursor [2-(1,5-dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-ylimino)acetic acid] was synthesised from 4-aminoantipyrine and glyoxylic acid, this precursor has been used in the synthesis of new multidentate ligand [2-((E)-3-(2-hydroxyphenylimino)-1,5-dimethyl-2-phenyl-2,3-dihydro-1H-pyrazol-4-ylimino)acetic acid][H2L] type (N2O2). The ligand was refluxed in ethanol with metal ions [VO(II), Mn(II), Co(II) and Ni(II)] salts to give complexes of general molecular formula:[M(H2L)2(X)(Y)].B, where: M=VO(II), X=0, Y=OSO3-2, B=2H2O; M=Mn(II),Co(II) ,X=Cl, Y=Cl, B=0; M=Ni(II), X=H2O, Y=Cl, B=Cl. These complexes were characterised by atomic absorpition(A.A), F.T-I.R., (U.V-Vis)spectroscopies (1H,13C NMR for ligand only), alon