Preparation and characterization of poly methyl methacrylate - sulfonated poly ether ether ketone with Gelatin hydrogel blend membranes for Environmental applications

Poly (methyl methacrylate) (PMMA) and Poly (methyl methacrylate)/Sulfonated poly (ether ether ketone) and Gelatin (SPEEK-GEL) blend membranes   were prepared by inversion technique in various composition using N, N’- dimethylformamide as solvent. These blend membranes   were characterized in terms of pure water flux, water content, porosity and thermal stability. The addition of SPEEK-GEL to the casting solution resulted in the higher pure water flux, water content and porosity. The cross sectional view of the blend membranes was performed with scanning electron microscopy. The effect of the addition of SPEEK-GEL in to the PMMA matrix on the above parameters was studied and the results were discussed. The influences of SPEEK-GEL concentration on permeate flux and rejection of blend membranes was examined by using aqueous Bovine Serum Albumin (BSA) protein solution. The influences of transmembrane pressure on permeate flux and rejection was also studied. This investigation was performed for assessing the environmental components in dairy waste water

Convolution Neural Network Based Brain Tumour Detection Using Efficient Classification Technique – A Robotics Approach

Medical image processing has become an important and essential element in the fields of biomedical and biological research such as tumor recognition and detection process is automatically determining the volume of a heart chamber and screening the brain scans for probable damages and diseases. Various techniques and methods for automatic detection and recognition of brain tumor which involved many steps viz. image acquisition through scan, segmentation of images, classification of images using neural network, optimization of developed images and identification of exact tumor category. This research paper dealt with a novel approach to identify and segment brain related tumors. The recognition and detection followed by segmentation of brain tumors can be formulized as novelty detection by using a new methodology of Hybrid probability based segmentation model which is straightened and bound. The main purpose and objective of this proposed novel method is to use precisely to identify the existence of tumour cells in brain images as an premature and early indication of malignant cells that may cause life threat and fatal to human beings