An Efficient Image Analysis Framework for the Classification of Glioma Brain Images Using CNN Approach

The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours.The detection of tumors is performed with the help of automatic computing technique as presented in the proposed work.The non-active cells in brain region are known to be benign and they will never cause the death of the patient.These non-active cells follow a uniform pattern in brain and have lower density than the surrounding pixels.The Magnetic Resonance(MR)image contrast is improved by the cost map construction technique.The deep learning algorithm for differentiating the normal brain MRI images from glioma cases is implemented in the proposed method.This technique permits to extract the linear features from the brain MR image and glioma tumors are detected based on these extracted features.Using k-mean clustering algorithm the tumor regions in glioma are classified.The proposed algorithm provides high sensitivity,specificity and tumor segmentation accuracy.

Physical chemical and biological characterization of a new bacteriocin produced by Bacillus cereus NS02

Objective:To screen the bacteriocinogenic isolate from buffalo milk and to characterize it on physical,chemical and biological aspects for the application in biopreservation.Methods:Bacillus cereus(B.cereus)was isolated and assessed for its baceteriocinogenic activity.Bacteriocin was produced and purified by ammonium sulphate precipitation,dialysis and gel filtration chromatography.Purified bacteriocin was used to clieck its antimicrobial activity against food borne bacteria.Effect and stability of bacteripcin was determined with the respect to temperature,pH,enzymes,organic solvents and chemicals.Bacteriocin was also subjected to SDS PAGE analysis to determine its molecular weight.In addition,functional groups exist in the bacteriocin was determined by FTIR analysis.Results:B.cereus was identified by 16S rRNA sequence analysis.Bacteriocin showed increased activity against all the bacteria used and its activity unit was found to be 51,200 AU/mL.It was stable to high temperature(100℃)and wide range of pH(3-10),sensitive to proteolytic enzymes and resistant to nonprotcolytic enzymes.It was low molecular weight(3.5-6 kDa)protein and FTIR study revealed the presence of amide group and NH stretching,Conclusions:Bacteriocin produced in this study possesses the highest antimicrobial activity against both gram positive and gram negative bacteria thereby it has immense application as biopreservative agent.FTIR proved its peptide nature.

Fuzzy Logic Based Handover Authentication in 5g Telecommunication Heterogeneous Networks

Under various deployment circumstances,fifth-generation(5G)telecommunications delivers improved network compound management with fast communication channels.Due to the introduction of the Internet of Things(IoT)in data management,the majority of the ultra-dense network models in 5G networks frequently have decreased spectral efficiency,weak handover management,and vulnerabilities.The majority of traditional handover authentication models are seriously threatened,making them vulnerable to a variety of security attacks.The authentication of networked devices is the most important issue.Therefore,a model that incorporates the handover mechanism and authentication model must be created.This article uses a fuzzy logic model to create a handover and key management system that focuses on cloud handover management and authentication performance.In order to decrease delays in 5G networks,the fuzzy logic is built with multiple criteria that aim to reduce the number of executed handovers and target cell selection.The simulation is run to evaluate the model’s performance in terms of latency,spatial complexity,and other metrics related to authentication attack validation.