Nitte Meenakshi Institute of Technology

About: Nitte Meenakshi Institute of Technology is a based out in . It is known for research contribution in the topics: Computer science & Ultimate tensile strength. The organization has 846 authors who have published 644 publications receiving 2702 citations.

Implementation of Bayesian Network Model (BN Trust Model) for IoT Routing

Abstract: In this paper, we are talking about the proposed Bayesian Network Trust Model (BN Trust Model). In attention to the developing issue of security of the Internet of Things, we present, from a quantifiable choice perspective, a novel methodology for trust-based access control utilizing Bayesian Network Model. We build up a trust model, BN Trust Model, which depicts a trust level for distinguishing proof organization in IoT. BN Trust Model is being actualized to record access control on trouble conditions where characters are not known in progress. A judgment will be favored dependent on standard parameters and be determined utilizing Bayesian choice rules. To evaluate a trust model, we play out an arithmetical investigation and reproduce it utilizing NS2 apparatus to look at control use. The activity result shows that the Bayesian choice hypothesis technique for BN Trust Model backings adaptability, and it is energy production as a creating number of devices and not influencing the working and execution work Model. BN Trust Model contrasted and different directing conventions of AODV, DSR, DSDV in the situation of two parameters parcel misfortune and Throughput. Result investigation shows that the proposed BN trust model gives better exactness thought about previous routing calculations.

SSVEP Based Correlation Analysis for Efficiency Enhancement of Brain-Computer Interfaces

Abstract: Recent progress in technologies and medical science have given momentum to Brain-computer interfaces (BCIs) system in generalizing human-computer communication, specifically for the people struggling with neuro-muscular disabilities. Currently, BCI systems heavily rely upon efficient electroencephalograms (EEG) signal detection from the current available solutions due to their noninvasiveness. However, the existing BCI systems works efficiently for less number of user instructions. Therefore, in this study, Adaptive Correlation based Component Analysis (ACCA) method is proposed to establish a proper Brain-computer interfaces (BCIs) system between user and computer. Here, correlation analysis is performed to identify spatial probability for a particular frequency using Adaptive Correlation based Component Analysis (ACCA) method. Maximum correlation between EEG signal phases triggered by both single and multiple flickers are generated using ACCA method to efficiently extract SSVEP component. The performance of proposed ACCA method is analysed against traditional SSVEP extraction methods in terms of classification accuracy, time consumption and Information Transfer Rate (ITR) for different subjects.

Seasonality, Quarterly Impact on Net Asset Value of Equity Linked Savings Schemes:

Abstract: This article attempts to (a) understand the quarterly seasonal behaviour of Net Asset Value of Equity Linked Savings Schemes (ELSS—Tax Saver Schemes), (b) analyse statistical significance of quarte...

Effect of Process Parameters on Centrifugally Cast Al‐Si FGM

Abstract: Functionally Graded Materials (FGM) are such kind of materials wherein the properties and structure are varied from one end of the cast to the other intentionally. Centrifuge technique has been used in this study to produce Al-Si FGMs. Several process parameters determine the microstructure and the distribution of phases in the FG casting. These parameters include the size and initial concentration of alloying element, the centrifugal force, solidification rate, cooling rate. In this work an attempt has been made to produce FGMs using three different process variables such as mold temperature, melt temperature and mold rotational speed, their effect on the structure and properties. For this study Al-17wt%Si is used. From the results it is seen that for a particular melt and mold temperatures by increasing the mold rotation speed enhances the segregation of the Si particles at the one end of the casting. Similarly increasing mold or melt temperature only, increases the segregation.