Rai A

Ramanathan S

Kannan R.J.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Quasi Opportunistic Supercomputing for Geospatial Socially Networked Mobile Devices

2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)

Learning visual models of object classes conventionally require hundreds or a large number of training samples. Conventional gradient-based approaches for target recognition require lot of data to be trained on and require exhaustive training with high computational expense. Hence, when a new condition or untrained data is encountered, such systems inadequately misconfigure newly learned feature sets in the trained model. This misconfigures the structure of re-learned features and is then carried out in subsequent recognition stages. Thus, a development in this scenario with low training time will allow us to fend of this disadvantage. This study presents a new automatic target recognition framework that gives the enhanced performance of target-recognition system when several imaging sensors are connected with one another. This is in contrast with traditional automatic target recognition frameworks, which utilizes one-on-one computational model over synthetic-aperture radar image-processing systems. The work comprises of a learning-based classifications strategy when dealing with sharing of learned parameters over the network to discern critical changes in target-recognition performance by utilizing a novel one-shot learning-based reconfigurable learning network for image processing platform. This upgrades the networked connected CCTV and multiview synthetic-aperture radar image object identification and recognition process.

The International Journal of Electrical Engineering & Education

One-shot learning technique regression of reconfigurable learning network for generative modeling in interconnected imaging infrastructure

This study presents a modeling method for control system of multi-coupled non-linear cyber physical system with the help of second-order dynamics of communicating membrane system of neuronal population based on a population coding algorithm. Here, the communicating membrane system is modeled based on several IoT devices connected in peer to peer form and the theory of fractional differential equations is as governing function over them. Here, the difficulty is in developing a collaborative learning algorithm for finding collaborative key points within high-dimensional decision space. In order to overcome such a problem, a gradient-based method is required to enable distributed control and collaborative decision making. Here, at every interval of the sampling time, all the subsystems are optimally synchronized in P population system by multiset-rewriting rules including the effect of symport/antiport systems. This is an interesting technical problem, related to the borderline between universality and non-universality of continuity of distributed coupling of multi-coupled control system. The presented study discusses the experimental proof of the algorithmic framework and model for SLAM operation. The consensus architecture in this domain will enable the development of evolving architecture of a non-linear cyber physical system. The close loop stability and the recursive feasibility of the evolved architecture are also studied. © The Author(s) 2019.

Consensus-based decision making in non-linearly multi-coupled IoT networked SLAM operations

2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)

Membrane Computing Based Scalable Distributed Learning and Collaborative Decision Making for Cyber Physical Systems

2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC)

Multi-user networked framework for virtual reality platform

Wireless networking technology is becoming increasingly popular but, at the same time, has introduced many security issues. WEP standards are followed in WLANs for providing security. But WEP is fatally crippled by the fact that WEP keys are the same for all users, all sessions and never changes and its poor implementation of the RC4 encryption scheme. The authentication mechanism is based on a simple challenge-response protocol. The main problem with the previously used method was same key was used for both encryption and authentication. But the proposed authentication is by means of certificates using Extensible Authentication Protocol and a session key is transferred after successful authentication between mobile node and server. This session key is then used for encrypting messages using Advanced Encryption Standard between mobile node and server.

Journal	Data powered by Typeset2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)
Publisher	Data powered by TypesetIEEE
Open Access	0