IoT Based Green House Monitoring Using Data Compressive Sensing Technique in WSN

Abstract Compressive Sampling is one of the important techniques for energy proficient transmission in wireless sensor. It is also utilized for low-sampling in several applications. Compressive sensing may reduce energy cost when sensor development is taken in to consideration. Green house farming is need of hour. Efficient management of resources is vital. An IOT based […]

A Hybrid Database Intrusion Detection Algorithm Using Swarm Intelligence and Radial Basis Function Network

Abstract Recently, all over the globe, intrusion detection especially in Database gaining lots of attentions from researchers as it serves a security support system to existing security mechanism. This paper presents a hybrid intrusion detection algorithm in Database System by making use of swarm intelligence and radial basis function network. Both these techniques are combined […]

Design and Analysis of RF MEMS Capacitive Shunt Switch and Impact of Geometric Trade-offs on RF Performance

Abstract The electromagnetic and the electromechanical characteristics of the radio frequency micro-electro-mechanicalsystem (RF MEMS) switches for high-frequency applications are the critical performance metrics that need to optimize. Performance indices of the RF MEMS switches such as isolation, insertion loss, pull-in voltage, holddown voltage, reliability are dependent on types and properties of conducting and insulating materials […]

A Hybrid Framework for Segmentation of MR Medical Images Using Adjusted Ant Colony Optimization

Abstract In this paper a new framework is suggested for segmentation of medical images (MRI) using hybrid optimization technique. This frame work includes de-nosing as image enhancement technique using discrete wavelet transform and initial segmentation is obtained by Hidden Markov random field model along with Kmeans clustering to get Maximum a posterior values (thresholds). The […]

A Framework for Brain Tumor Classification and Grade Detection from Magnetic Resonance Image

Abstract Brain tumor is a serious disease and numbers of affected people are drastically increasing day by day and researchers are focused on detection and classification of such types of severe diseases so that appropriate diagnosis can be provided to patient. In medical science, manually detection of brain tumor using medical resonance image by radiologist […]