Case-based reasoning system for assessing water pollution / Asmaa Hashem Abdeltawab ; Supervised Osman Mohammed Hegazy , Aboul Ella Hassanien , Nashwa Elbendary

Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information System

Water pollution by organic materials or metals is one of the problems that threaten humanity, both nowadays and over the next decades. Morphological changes in Nile Tilapia 3Oreochromis niloticus3 {uFB01}sh liver and gills can also represent the adaptation strategies to main- tain some physiological functions or to assess acute and chronic expo- sure to chemicals found in water and sediments. This thesis provides an automatic system for assessing water pollution; in Sharkia gover- norate - Egypt, based on microscopic images of {uFB01}sh gills and liver. The proposed system used {uFB01}sh gills and liver as hybrid biomarker to detect water pollution. It utilized case based reasoning (CBR) for indicating the degree of water pollution based on the di{uFB00}erent histopathological changes in {uFB01}sh gills and liver microscopic images. Various performance evaluation metrics; namely, retrieval accuracy, Receiver Operating Characteristic (ROC) curves, F-measure, and G- mean, have been used in order to objectively indicate the true perfor- mance of the system considering the unbalanced data. Experimental results showed that the proposed hybrid biomarker CBR based sys- tem achieved water quality prediction accuracy of 97.9 % using cosine distance similarity measure. Also, it outperformed both SVMs and LDA classi{uFB01}ers for the tested microscopic images data set

Issued also as CD