Institution
Christ University
Education•Bengaluru, India•
About: Christ University is a education organization based out in Bengaluru, India. It is known for research contribution in the topics: Computer science & Convection. The organization has 2267 authors who have published 2715 publications receiving 14575 citations. The organization is also known as: Christ College & Christ University.
Topics: Computer science, Convection, Population, Cloud computing, Heat transfer
Papers published on a yearly basis
Papers
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01 Jan 2020TL;DR: A signature-based authentication protocol for remote health monitoring that is resistant to various common and automated attacks and does not require the server to maintain a password table is presented.
Abstract: Remote health monitoring can offer a lot of advantage to all the players in healthcare industry and it can contribute to reduced healthcare expenses. Wireless medical sensor networks capable of accumulating and transferring vital parameters of patients play a crucial role in remote health monitoring. Security and privacy are major concerns preventing the patients from adopting this technology with an open mind. This paper presents a signature-based authentication protocol for remote health monitoring. The work also discusses an authentication protocol for the mutual authentication of users and medical server. The protocol does not require the server to maintain a password table. The proposed algorithms are resistant to various attacks such as replay attack, stolen verifier attack, and privileged insider attack. The work includes the informal and formal security analysis of the proposed protocols. Scyther tool is used for formal security analysis and the results show that the protocol is resistant to various common and automated attacks.
9 citations
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Abstract: Inverse cubic law has been an established Econophysics law. However, it has been only carried out on the distribution tails of the log returns of different asset classes (stocks, commodities, etc.). Financial Reynolds number, an Econophysics proxy for bourse volatility has been tested here with Hill estimator to find similar outcome. The Tail exponent or α ≈ 3, is found to be well outside the Levy regime (0 < α < 2). This confirms that asymptotic decay pattern for the cumulative distribution in fat tails following inverse cubic law. Hence, volatility like stock returns also follow inverse cubic law, thus stay way outside the Levy regime. This piece of work finds the volatility proxy (econophysical) to be following asymptotic decay with tail exponent or α ≈ 3, or, in simple terms, ‘inverse cubic law’. Risk (volatility proxy) and return (log returns) being two inseparable components of quantitative finance have been found to follow the similar law as well. Hence, inverse cubic law truly becomes universal in quantitative finance.
9 citations
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TL;DR: In this paper, a graceful amalgamation of Laplace transform with q-homotopy analysis algorithm and Atangana-Baleanu (AB) operator is proposed to exemplify the behavior of the nonlinear model of arbitrary order differential equations.
9 citations
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TL;DR: In this paper, Rainbow Neighbors of a graph G are defined as the closed neighborhoods of a vertex that contain at least one coloured vertex of each colour in the chromatic colouring of G. The number of vertices in G yielding rainbow neighbourhoods is called the rainbow neighbourhood number.
Abstract: A rainbow neighbourhood of a graph G is the closed neighbourhood N[v] of a vertex $$v \in V(G)$$
which contains at least one coloured vertex of each colour in the chromatic colouring $${\mathscr {C}}$$
of G.
Let G be a graph with a chromatic colouring $${\mathscr {C}}$$
defined on it. The number of vertices in G yielding rainbow neighbourhoods is called the rainbow neighbourhood number of the graph G, denoted by $$r_\chi (G)$$
. Rainbow neighbourhood number of the complements and products of certain fundamental graph classes are discussed in this paper.
9 citations
Authors
Showing all 2404 results
Name | H-index | Papers | Citations |
---|---|---|---|
Matt S. Owers | 56 | 217 | 8765 |
Bijjanal Jayanna Gireesha | 40 | 233 | 4748 |
Basavarajappa Mahanthesh | 38 | 158 | 3580 |
Madhavi Rangaswamy | 31 | 52 | 3063 |
Siddhartha Bhattacharyya | 30 | 251 | 3481 |
Rohan Fernandes | 28 | 55 | 2585 |
Gurumurthy Hegde | 27 | 176 | 2185 |
Pundikala Veeresha | 27 | 67 | 1825 |
Pradeep G. Siddheshwar | 26 | 156 | 2298 |
Renjith S. Pillai | 25 | 65 | 2663 |
Brij Kumar Dhindaw | 25 | 123 | 2224 |
Sukalyan Dash | 24 | 137 | 2682 |
Anil Agarwal | 21 | 185 | 1695 |
Maggi Banning | 20 | 73 | 1695 |
Lakshmi S. Iyer | 19 | 123 | 2276 |