Preferred Language
Articles
/
bsj-4912
Evaluation of Some Trace Elements Pollution in Sediments of the Tigris River in Wasit Governorate, Iraq
...Show More Authors

The main objectives of present study are to evaluate the trace elements pollution in the sediment of the Tigris River and drainage canals in Wasit Governorate, Iraq. Assessment of trace elements pollutants were conducted for 18 sediment samples collected in March 2017. Trace elements were analyzed in sediment Tigris River samples in Wasit Governorate. This metal pollution was evaluated using geo-accumulation (I-geo) index, Contamination Factor (CF) and Pollution Load Index (PLI). According to  these statistical indices, the sediments collected from Tigris River in the study area are highly polluted with Titanium (71.9 ppm), Nickel (226.6 ppm) Chromium (425.2 ppm), Cadmium (2ppm) and Molybdenum (15.8 ppm) while  the sediments  were moderately polluted with Cobalt (25.1 ppm), Strontium (839.3 ppm), Copper (56.2), Manganese (106.1ppm), Vanadium (135 ppm), Niobium (9.79 ppm). However, the sediments of the Tigris River is not polluted by Lead, Barium, Gallium, Rubidium and, Zinc.  Metals concentration levels in the sediments of the drainage canals that discharged into the Tigris River showed higher concentrations  than  the Tigris sediments in Ta, V, Ni, Cu, Ga, Br, Sr and Mo.

Scopus Clarivate Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Bridge Regression Model Estimating via Simulation
...Show More Authors

      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

... Show More
View Publication Preview PDF
Crossref