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Spent caustic treatment using hydrophobic room temperatures ionic liquids
Muhammad Ashraf Sabri,Taleb Hassan Ibrahim,Mustafa Ibrahim Khamis,Paul Nancarrow,Muhammad Faheem Hassan 한국공업화학회 2018 Journal of Industrial and Engineering Chemistry Vol.65 No.-
Two hydrophobic room temperature ionic liquid (IL), tetrahexylammonium dihexyl-sulfosuccinate (IL1) and trioctylmethylammonium salicylate (IL2), have been employed for the treatment of spent caustic (SC) wastewater by liquid–liquid extraction at room temperature and pressure. The concentrations of phenols, thiols and benzaldehyde were reduced to below their detection limits and the chemical oxygen demand (COD) levels were reduced from 64166 ± 3880 mg/l to 63.0 ± 9.0 mg/l. This represents an outstanding reduction in pollutant and COD levels to well below the discharge limits for industrial effluents as set by U.S.A. Environmental Protection Agency (EPA) regulations, thus eliminating the need for any further treatment before discharge.
Brain Tumor Prediction through Behavior Analysis of Cells Growth Using Machine Learning Techniques
Nouh Sabri Elmitwally,Muhammad Aqib Freed,Muhammad Waseem Iqbal,Aasma Ashraf,Farukh Muneem,Muhammad Aqeel 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10
Brain tumor is a very terrible disease. Brain tumor is caused by an increased number of cells. The presence of the skull layer around the brain makes it tough in studying the behavior of growth cells. It also raises the complication for the identification of disease. The initial discovery of a brain tumor is necessary to defend the survival of patients. Frequently, the brain cancer segmentation, and classification through the MRI images technique. Though, the radiologists are not providing actual visualization of brain cells in MRI images due to the irregular growth of cells, which forms of cells are growing rapidly and slow at some stage in brain tumors in the brain. So, automatic strategies are required to evaluate thoughts tumors exactly from MRI images in this research automatic, MRI brain tumors are used for classification, segmentation, and Behavior analysis of cell growth. The problem of visualization of cell growth and behavior analysis of brain cells is solved through MRI images which enhance the detection of cancer. To analyze the behavior of cell growth, which forms of cells are growing rapidly and slow at some stage in brain tumors, and analyze the area of images in which type of cells is affected. Single models are less efficient. We will use ensemble models which would also be helpful for better performance and accuracy.