Analysis of BrainMRI: AI-Assisted Healthcare Framework for the Smart Cities

The use of intelligent machines to work and react like humans is vital in emerging smart cities.Computer-aided analysis of complex and huge MRI(Mag-netic Resonance Imaging)scans is very important in healthcare applications.Among AI(Artificial Intelligence)driven healthcare applications,tumor detection is one of the contemporary researchfields that have become attractive to research-ers.There are several modalities of imaging performed on the brain for the pur-pose of tumor detection.This paper offers a deep learning approach for detecting brain tumors from MR(Magnetic Resonance)images based on changes in the division of the training and testing data and the structure of the CNN(Convolu-tional Neural Network)layers.The proposed approach is carried out on a brain tumor dataset from the National Centre of Image-Guided Therapy,including about 4700 MRI images of ten brain tumor cases with both normal and abnormal states.The dataset is divided into test,and train subsets with a ratio of the training set to the validation set of 70:30.The main contribution of this paper is introdu-cing an optimum deep learning structure of CNN layers.The simulation results are obtained for 50 epochs in the training phase.The simulation results reveal that the optimum CNN architecture consists of four layers.

Cancellable Multi-Biometric Feature Veins Template Generation Based on SHA-3 Hashing

In this paper,a novel cancellable biometrics technique calledMulti-Biometric-Feature-Hashing(MBFH)is proposed.The MBFH strategy is utilized to actualize a single direction(non-invertibility)biometric shape.MBFH is a typical model security conspire that is distinguished in the utilization of this protection insurance framework in numerous sorts of biometric feature strategies(retina,palm print,Hand Dorsum,fingerprint).A more robust and accurate multilingual biological structure in expressing human loneliness requires a different format to record clients with inseparable comparisons from individual biographical sources.This may raise worries about their utilization and security when these spread out designs are subverted as everybody is acknowledged for another biometric attribute.The proposed structure comprises of four sections:input multi-biometric acquisition,feature extraction,Multi-Exposure Fusion(MEF)and secure hashing calculation(SHA-3).Multimodal biometrics systems that are more powerful and precise in human-unmistakable evidence require various configurations to store a comparative customer that can be contrasted with biometric wellsprings of people.Disparate top words,biometrics graphs can’t be denied and change to another request for positive Identifications(IDs)while settling.Cancellable biometrics is may be the special procedure used to recognize this issue.

Ultra-flexible graphene/nylon/PDMS coaxial fiber-shaped multifunctional sensor

The development of flexible and wearable devices is mainly required for tactile sensing;as such devices can adapt to complicated nonuniform surfaces,they can be applied to the human body.Nevertheless,it remains necessary to simultaneously achieve small-scale,portable,and stable developments in such devices.Thus,this work aims at fabricating a novel,lightweight,ultra-flexible,and fiber-shaped coaxial structure with a diameter of 0.51 mm using polydimethylsiloxane/graphene/nylon material,based on piezoresistive and triboelectric principles.The piezoresistive-based robotic-hand-controlled sensor thus realized exhibits a response time of 120 ms and a fast recovery time of 55 ms.Further,the piezoresistive-based sensors effectively feature whisker/joystick-guided behaviors and also sense the human finger contact.Owing to the triboelectric-based selfpowered nanogenerator behavior,the resulting sensor can convert mechanical motion into electrical energy,without adversely affecting human organs.Moreover,this triboelectric-based human finger sensor can be operated under different bending modes at specific angles.Notably,this multifunctional sensor is cost-effective and suitable for various applications,including robotichand-controlled operations in medical surgery,whisker/joystick motions in lightweight drone technology,and navigation with highsensitivity components.