Abstract: There are many classical algorithms for finding
routing in FPGA. But Using DNA computing we can solve the routes
efficiently and fast. The run time complexity of DNA algorithms is
much less than other classical algorithms which are used for solving
routing in FPGA. The research in DNA computing is in a primary
level. High information density of DNA molecules and massive
parallelism involved in the DNA reactions make DNA computing a
powerful tool. It has been proved by many research accomplishments
that any procedure that can be programmed in a silicon computer can
be realized as a DNA computing procedure. In this paper we have
proposed two tier approaches for the FPGA routing solution. First,
geometric FPGA detailed routing task is solved by transforming it
into a Boolean satisfiability equation with the property that any
assignment of input variables that satisfies the equation specifies a
valid routing. Satisfying assignment for particular route will result in
a valid routing and absence of a satisfying assignment implies that
the layout is un-routable. In second step, DNA search algorithm is
applied on this Boolean equation for solving routing alternatives
utilizing the properties of DNA computation. The simulated results
are satisfactory and give the indication of applicability of DNA
computing for solving the FPGA Routing problem.
Abstract: Software Reusability is primary attribute of software
quality. There are metrics for identifying the quality of reusable
components but the function that makes use of these metrics to find
reusability of software components is still not clear. These metrics if
identified in the design phase or even in the coding phase can help us
to reduce the rework by improving quality of reuse of the component
and hence improve the productivity due to probabilistic increase in
the reuse level. In this paper, we have devised the framework of
metrics that uses McCabe-s Cyclometric Complexity Measure for
Complexity measurement, Regularity Metric, Halstead Software
Science Indicator for Volume indication, Reuse Frequency metric
and Coupling Metric values of the software component as input
attributes and calculated reusability of the software component. Here,
comparative analysis of the fuzzy, Neuro-fuzzy and Fuzzy-GA
approaches is performed to evaluate the reusability of software
components and Fuzzy-GA results outperform the other used
approaches. The developed reusability model has produced high
precision results as expected by the human experts.
Abstract: Metrics is the process by which numbers or symbols
are assigned to attributes of entities in the real world in such a way as
to describe them according to clearly defined rules. Software metrics
are instruments or ways to measuring all the aspect of software
product. These metrics are used throughout a software project to
assist in estimation, quality control, productivity assessment, and
project control. Object oriented software metrics focus on
measurements that are applied to the class and other characteristics.
These measurements convey the software engineer to the behavior of
the software and how changes can be made that will reduce
complexity and improve the continuing capability of the software.
Object oriented software metric can be classified in two types static
and dynamic. Static metrics are concerned with all the aspects of
measuring by static analysis of software and dynamic metrics are
concerned with all the measuring aspect of the software at run time.
Major work done before, was focusing on static metric. Also some
work has been done in the field of dynamic nature of the software
measurements. But research in this area is demanding for more work.
In this paper we give a set of dynamic metrics specifically for
polymorphism in object oriented system.
Abstract: Protein structure determination and prediction has
been a focal research subject in the field of bioinformatics due to the
importance of protein structure in understanding the biological and
chemical activities of organisms. The experimental methods used by
biotechnologists to determine the structures of proteins demand
sophisticated equipment and time. A host of computational methods
are developed to predict the location of secondary structure elements
in proteins for complementing or creating insights into experimental
results. However, prediction accuracies of these methods rarely
exceed 70%.
Abstract: Hybridization refers to the crossing breeding of two
plants. Coefficient of Parentage (COP) is used by the plant breeders
to determine the genetic diversity across various varieties so as to
incorporate the useful characters of the two varieties to develop a
new crop variety with particular useful characters. Genetic Diversity
is the prerequisite for any cultivar development program. Genetic
Diversity depends upon the pedigree information of the varieties
based on particular levels. Pedigree refers to the parents of a
particular variety at various levels. This paper discusses the searching
and analyses of different possible pairs of varieties selected on the
basis of morphological characters, Climatic conditions and Nutrients
so as to obtain the most optimal pair that can produce the required
crossbreed variety. An algorithm was developed to determine the
coefficient of parentage (COP) between the selected wheat varieties.
Dummy values were used wherever actual data was not available.
Abstract: Phylogenetic tree is a graphical representation of the
evolutionary relationship among three or more genes or organisms.
These trees show relatedness of data sets, species or genes
divergence time and nature of their common ancestors. Quality of a
phylogenetic tree requires parsimony criterion. Various approaches
have been proposed for constructing most parsimonious trees. This
paper is concerned about calculating and optimizing the changes of
state that are needed called Small Parsimony Algorithms. This paper
has proposed enhanced small parsimony algorithm to give better
score based on number of evolutionary changes needed to produce
the observed sequence changes tree and also give the ancestor of the
given input.