S. Karthikeyan ¹, R. Prasad ¹, T. S. Mahendran ¹, K. Rajagopal ¹, V. Ravendran ²

Affiliations
1 Department of Biotechnology, Vel’ s University, Pallavaram, Chennai 600 117, IN
2 Department of Botany, Madras Christian College, Chennai 600 059, IN

Abstract

This study reports a simple micropropagation protocol and thereby rapid multiplication of the useful medicinal plant- Scoparia dulcis L. Single node explants were inoculated on basal MS medium containing 3% (w/v) sucrose, supplemented with different concentrations and combinations of 6-benzylaminopurine (BAP), kinetin (KN), indole-3-acetic acid (IAA), indole-3-butyric acid (IBA) and Naphthalene acetic acid (NAA) for direct plant regeneration. Maximum numbers of shoot (~22) were observed on the medium containing 0.5 mg/l BAP and 0.25 mg/l IAA after four weeks of culture. Regenerated shoots were separated and ischolar_mained on half strength MS medium supplemented with 0.5 mg/l of IBA alone for three weeks. Simultaneous regeneration of shoots and ischolar_mains and in vitro flowering were achieved from the nodal explants on MS medium supplemented with 0.5 mg/l KN and 2.0 mg/l IAA. Well-developed complete plantlets were transferred on to specially made plastic cup containing soil rite. Acclimatized plantlets were successfully grown in garden soil.

Keywords

Scoparia dulcis, Nodal Explants, Micropropagation, Plant Tissue Culture

Full Text

   

R. Ananth ¹, S. Karthikeyan ¹

Affiliations
1 Sathyabama University, Agni College of Technology, Chennai – 600130, Tamil Nadu, IN

Abstract

Objectives: In cluster based algorithms, the group head needs to do the transmission, gathering, aggregation, collection and the timing administration. Due to this the head of the cluster will lose its energy rapidly and another head ought to be found. A new election process creates unwelcome control message movement in that particular network. The main objective is to reduce the number of elections hence the wastage of energy can be minimized. Methods/Statistical Analysis: To reduce the number of election we propose our model Dual Cluster Head Protocol (DCH). The key idea is to have a group head and sub group head, where the work load will be shared between them. The sub head will perform the information gathering and aggregation inside the cluster and it will report just to the main cluster head. The clusters will be managed by the Sub-Cluster Head (SCH) node, but the session management will be carried out by the cluster head. All the outward communications will be carried out by main cluster head; also it relays the information from other heads. Findings: Our algorithm uses lesser amount of control messages than other conventional algorithms since the number of cluster head re-elections is reduced. The performance of the algorithm matches with protocols like LEACH and SEECH. We have used 3 scenarios for testing the protocol; in the first scenario with 100 nodes DCH protocol performed 31% better than SEECH and 86% better than LEACH. In second scenario with 400 nodes DCH protocol performed 6% better than SEECH and 20% better than LEACH. In third scenario with 1000 nodes DCH protocol performed 38% better than LEACH but fell short of 45% when compared with SEECH. Application/Improvements: Right now the algorithm performs well in low and medium density sensor fields. It can be improved to work efficiently in high density sensor fields. The comparison can be made with newer protocols like HEED

Keywords

Aggregation, Clustering, Dual Cluster Head, Routing.

Full Text

   

R. Bagavath Sri ¹, S. Karthikeyan ¹

Affiliations
1 Sathyabama University, Chennai - 600119, Tamil Nadu, IN

Abstract

In medical field, patients generally need highly equipped systems because of their inability to access emergency systems. In such situation, high level of security must be ensured to prevent fatal medical errors. RFID technology is generally used in the medical environment. Applications of elliptic curve algorithm are considered and several cryptography modules are analyzed. Heavy weight schemes are considered to be highly secure. Security drawbacks have been analyzed in Godor and Imre scheme in terms of maximum delay and running time and improved encryption and decryption scheme has been proposed. The proposed algorithm has been simulated in Xilinx 14.5 ISE and worst case slack, running time and frequency has been analyzed.

Keywords

Desynchronisation Attacks, DOS Attacks, Elliptic Curve Cryptography, IoT, RFID Technology, Server Spoofing Attacks.

Full Text

   

S. Karthikeyan ¹, E. J. Thomson Fredrik ¹

Affiliations
1 Department of Computer Science, Karpagam University, Coimbatore - 641021, Tamil Nadu, IN

Abstract

Objectives: Extracting relevant information from large database is attaining huge significance. Clustering of relevant information from large database becomes difficult. The major objective of this work is to proposed novel clustering methods for solving clustering problem. Methods/Statistical Analysis: This proposed work introduces possibility of a novel approach Hybrid Artificial Bee Colony-Firefly Algorithm (HABC-FA) for clustering to solve the clustering problem in the benchmark datasets like Fisher’s iris dataset. Here this FA incorporates its genome behavior of fireflies to accomplish the optimal clustering solution with ABC. The performance of this novel algorithm Hybrid ABC-FA is then compared with existing clustering algorithms like the ABC and hybrid Particle Swarm Artificial Bee Colony (PSABC) with regard to different statistical criteria making use three different types of benchmark datasets. Findings: The experimentation results prove that the proposed scheme performs better than the existing Swarm Intelligence (SI) based algorithms like ABC and PSABC in terms of speed and success rate and the proposed HABC-FA algorithm performance evaluates by using clustering parameters like recall, precision and F-measure. Application/Improvements: HABC-FA is proposed for the purpose of solving the clustering problem in the benchmark datasets like Fisher’s iris dataset

Keywords

Artificial Bee Colony Algorithm (ABC), ABC-Particle Swarm Optimisation (PSO) (PSABC), Clustering, Hybrid Artificial Bee Colony with Firefly Algorithm (HABC-FA), Swarm Intelligence (SI).

Full Text