44 research outputs found
Swarm Intelligence
Biologically inspired computing is an area of computer science which uses the
advantageous properties of biological systems. It is the amalgamation of
computational intelligence and collective intelligence. Biologically inspired
mechanisms have already proved successful in achieving major advances in a wide
range of problems in computing and communication systems. The consortium of
bio-inspired computing are artificial neural networks, evolutionary algorithms,
swarm intelligence, artificial immune systems, fractal geometry, DNA computing
and quantum computing, etc. This article gives an introduction to swarm
intelligence
An Introduction to Knowledge Management
Knowledge has been lately recognized as one of the most important assets of
organizations. Managing knowledge has grown to be imperative for the success of
a company. This paper presents an overview of Knowledge Management and various
aspects of secure knowledge management. A case study of knowledge management
activities at Tata Steel is also discusse
Review of Replication Schemes for Unstructured P2P Networks
To improve unstructured P2P system performance, one wants to minimize the
number of peers that have to be probed for the shortening of the search time. A
solution to the problem is to employ a replication scheme, which provides high
hit rate for target files. Replication can also provide load balancing and
reduce access latency if the file is accessed by a large population of users.
This paper briefly describes various replication schemes that have appeared in
the literature and also focuses on a novel replication technique called
Q-replication to increase availability of objects in unstructured P2P networks.
The Q-replication technique replicates objects autonomously to suitable sites
based on object popularity and site selection logic by extensively employing
Q-learning concept.Comment: 7 page
Survey of Search and Replication Schemes in Unstructured P2P Networks
P2P computing lifts taxing issues in various areas of computer science. The
largely used decentralized unstructured P2P systems are ad hoc in nature and
present a number of research challenges. In this paper, we provide a
comprehensive theoretical survey of various state-of-the-art search and
replication schemes in unstructured P2P networks for file-sharing applications.
The classifications of search and replication techniques and their advantages
and disadvantages are briefly explained. Finally, the various issues on
searching and replication for unstructured P2P networks are discussed.Comment: 39 Pages 5 Figure
Securing Biometric Images using Reversible Watermarking
Biometric security is a fast growing area. Protecting biometric data is very
important since it can be misused by attackers. In order to increase security
of biometric data there are different methods in which watermarking is widely
accepted. A more acceptable, new important development in this area is
reversible watermarking in which the original image can be completely restored
and the watermark can be retrieved. But reversible watermarking in biometrics
is an understudied area. Reversible watermarking maintains high quality of
biometric data. This paper proposes Rotational Replacement of LSB as a
reversible watermarking scheme for biometric images. PSNR is the regular method
used for quality measurement of biometric data. In this paper we also show that
SSIM Index is a better alternate for effective quality assessment for
reversible watermarked biometric data by comparing with the well known
reversible watermarking scheme using Difference Expansion.Comment: 8 pages, 7 figure
Introduction to Bioinformatics
Bioinformatics is a new discipline that addresses the need to manage and
interpret the data that in the past decade was massively generated by genomic
research. This discipline represents the convergence of genomics, biotechnology
and information technology, and encompasses analysis and interpretation of
data, modeling of biological phenomena, and development of algorithms and
statistics. This article presents an introduction to bioinformatic
A System for Predicting Subcellular Localization of Yeast Genome Using Neural Network
The subcellular location of a protein can provide valuable information about
its function. With the rapid increase of sequenced genomic data, the need for
an automated and accurate tool to predict subcellular localization becomes
increasingly important. Many efforts have been made to predict protein
subcellular localization. This paper aims to merge the artificial neural
networks and bioinformatics to predict the location of protein in yeast genome.
We introduce a new subcellular prediction method based on a backpropagation
neural network. The results show that the prediction within an error limit of 5
to 10 percentage can be achieved with the system
Introduction to Distributed Systems
Computing has passed through many transformations since the birth of the
first computing machines. Developments in technology have resulted in the
availability of fast and inexpensive processors, and progresses in
communication technology have resulted in the availability of lucrative and
highly proficient computer networks. Among these, the centralized networks have
one component that is shared by users all the time. All resources are
accessible, but there is a single point of control as well as a single point of
failure. The integration of computer and networking technologies gave birth to
new paradigm of computing called distributed computing in the late 1970s.
Distributed computing has changed the face of computing and offered quick and
precise solutions for a variety of complex problems for different fields.
Nowadays, we are fully engrossed by the information age, and expending more
time communicating and gathering information through the Internet. The Internet
keeps on progressing along more than a few magnitudes, abiding end systems
increasingly to communicate in more and more different ways. Over the years,
several methods have evolved to enable these developments, ranging from
simplistic data sharing to advanced systems supporting a multitude of services.
This article provides an overview of distributed computing systems. The
definition, architecture, characteristics of distributed systems and the
various distributed computing fallacies are discussed in the beginning.
Finally, discusses client/server computing, World Wide Web and types of
distributed systems
Information Hiding Techniques: A Tutorial Review
The purpose of this tutorial is to present an overview of various information
hiding techniques. A brief history of steganography is provided along with
techniques that were used to hide information. Text, image and audio based
information hiding techniques are discussed. This paper also provides a basic
introduction to digital watermarking
A Fast Heuristic Algorithm Based on Verification and Elimination Methods for Maximum Clique Problem
A clique in an undirected graph G= (V, E) is a subset V' V of vertices, each
pair of which is connected by an edge in E. The clique problem is an
optimization problem of finding a clique of maximum size in graph. The clique
problem is NP-Complete. We have succeeded in developing a fast algorithm for
maximum clique problem by employing the method of verification and elimination.
For a graph of size N there are 2N sub graphs, which may be cliques and hence
verifying all of them, will take a long time. Idea is to eliminate a major
number of sub graphs, which cannot be cliques and verifying only the remaining
sub graphs. This heuristic algorithm runs in polynomial time and executes
successfully for several examples when applied to random graphs and DIMACS
benchmark graphs.Comment: 06 pages,01 figure