BIO INFORMATICS AND BIO SCIENCE Research 2018-2019

Raja Mohamed S and Raviraj P

ABSTRACT
Robot design complexity is increasing day by day especially in automated industries. In this paper we propose biologically inspired design framework for robots in dynamic world on the basis of Co-Evolution, Virtual Ecology, Life time learning which are derived from biological creatures. We have created a virtual khepera robot in Framsticks and tested its operational credibility in terms hardware and software components by applying the above suggested techniques. Monitoring complex and non complex behaviors in different environments and obtaining the parameters that influence software and hardware design of the robot that influence anticipated and unanticipated failures, control programs of robot generation are the major concerns of our techniques.

KEYWORDS

Biology, Khepera, Framsticks, Framework, Simulation.

For More Details: https://wireilla.com/papers/ijbb/V1N1/1011ijbb03.pdf

Shrikant Sharma, Shashank Rana

Abstract

In-silico study was carried out to study motifs present in precursors of antimicrobial, antithrombotic, casein derived and mineral binding bioactive peptides by using online servers. MEME suite was used for defining the common consensus pattern present in bioactive peptides precursors. It was found that although three different consensus patterns was identified in precursors but theses consensus pattern overlapped in many sequences and all three motifs may be present in many peptides precursor sequences.

Keywords

In-Silico study, Bio-active peptides, MEME Suite, Consensus pattern.

For More Details: https://wireilla.com/papers/ijbb/V1N1/1011ijbb02.pdf

https://wireilla.com/ijbb/vol1.html

 

Sundarapandian Vaidyanathan

ABSTRACT

The Lotka-Volterra equations are a system of equations proposed to provide a simplified model of twospecies predator-prey population dynamics. In this paper, we investigate the problem of adaptive chaos control and synchronization of a generalized Lotka-Volterra system discovered by Samardzija and Greller (1988). The Samardzija-Greller model is a two-predator, one-prey generalization of the Lotka-Volterra system. First, adaptive control laws are designed to stabilize the generalized Lotka-Volterra system to its unstable equilibrium point at the origin based on the adaptive control theory and Lyapunov stability theory. Then adaptive control laws are derived to achieve global chaos synchronization of identical generalized Lotka-Volterra systems with unknown parameters. Numerical simulations are shown to validate and demonstrate the effectiveness of the proposed adaptive control and synchronization schemes for the generalized Lotka-Volterra system.

KEYWORDS

Adaptive Control, Stabilization, Chaos Synchronization, Generalized Lotka-Volterra Chaotic System.

For More Details: https://wireilla.com/papers/ijbb/V1N1/1011ijbb01.pdf

https://wireilla.com/ijbb/vol1.html