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Issue : April
2009
DOI: AA042009001
Title: Dynamic Motion Planning of Mobile Robot with
Fuzzy Approach
Authors: S. R. Tandan, R. Sahay, and N. Verma
Keywords: Dynamic Motion Planning, Fuzzy Logic Controller,
Fuzzy Logic System
Abstract:
One of the key challenges in Dynamic Motion
Planning of Mobile Robots is navigation in environment
that are cluttered with obstacle. Motion planning
becomes more complex when the configuration and position
of obstacle are not known priori for such system Soft
Computing Techniques are popularly used. Due to the
dynamic uncertainties posed by the vary nature of
the problem use of Fuzzy Approach makes the handling
the task easier. In this paper a solution is proposed
for dynamic motion planning of Mobile Robot with and
without obstacle. A Fuzzy Logic Controller is design
as a solution to the problem.
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Issue : April 2009
DOI: AA042009002
Title: A New Evolutionary Algorithm Based on Cellular
Automata
Authors: Tapas Kumar, IMS Lamba, G. Sahoo
Keywords: Fitness Analysis, Genetic Algorithm, CA-EA
Model, Cellular Automata
Abstract:
The field of evolutionary computation is itself
an evolving community of people, ideas, and applications.
To derive a solution of a problem from a population
of individuals, over a number of generations, evolutionary
computing techniques has been used as an explicit
function. In this paper a new evolutionary algorithm,
called the CA-EA (Cellular Automata Based Evolutionary
Algorithm), is proposed. This algorithm is a combination
of evolutionary algorithms and the Cellular Automata
(CA). Our motivation here is to discuss how cellular
automata techniques can be involved on evolutionary
algorithm. A study of cellular automata based evolutionary
computation in genetic analysis is an inherent problem.
But the key problems of genetic analysis are very
sensitive in the detection of fitness cells. Here,
we consider an interactive step so as to get a maximum
amount of information that can be shared for the best
evaluation of individual fitness cell.
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Issue : April 2009
DOI: AA042009003
Title: Temporal-Hmine-rev algorithm for Mining Frequent
Patterns in Temporal Databases
Authors: M. Krishnamurthy, A. Kannan, R. Baskaran
and K. Mythili
Keywords: Association Rule, Calendar Schema, Frequent
Patterns, H-Struct, Temporal Association Rules
Abstract:
A temporal association rule is an association
rule that holds during specific time intervals. The
problem is to discover complete set of frequent patterns
with respect to calendar schema from a set of time
stamped transactions. This paper uses the data structure
H-struct (Hyper-structure) of Hmine-rev, and incorporated
temporal aspects and it is called T-Hmine-rev (Temporal-Hmine
-reverse). Hmine-rev is a revised algorithm of H-mine(Hyper-structure
mining) which is used for mining frequent patterns
and it does not need any adjustment of H-struct links
structure like H-mine.Hmine-rev works well on sparse
dataset and H-struct is used for fast mining on time-based
dataset.
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Issue : April 2009
DOI: AA042009004
Title: Automatic Keyword and Content-Based Image Retrieval
by Intelligent Clustering Techniques
Authors: S. Vinodkumar, P.R. Lakshmi
Keywords: Image Retrieval, CBIR, Keyword Based Image
Retrieval
Abstract:
The CLUster-based rEtrieval(CLUE), groups the
image based on the similarity measure, so that there
is maximum similarity with in the cluster and minimum
similarity between the two cluster and then retrieve
the images related to the query. The cluster based
retrieval of images tackles the semantic gap problem.
The Content-Based Image Retrieval (CBIR) extract the
feature of the images and the images with maximum
similarity with that of the query is retrieved. This
paper makes use of both the concept to retrieve the
images. The CBIR system-using CLUE is called as Content-Based
Image Clusters Retrieval (CBICR).The keyword-based
retrieval along with the CBIR system retrieves the
relevant images more effectively and it consumes less
amount of time. The keyword based retrieval is done
and the Nearest Neighbor Method is used to locate
neighbor of the target image. The N-cut algorithm
is used to organize the cluster.
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Issue : April 2009
DOI: AA042009005
Title: Separation of Tamil and Devanagari Script Words
in Printed Bilingual Document Images
Authors: R. Rathinapriya, S. Abirami and B. Manjula
Keywords: Bi-lingual document, Script Identification,
Rule Based Classification, Optical Character Recognition
(OCR)
Abstract:
Identification of scripts from bi-script document
is one of the important steps in the design of an
OCR system for successful analysis and recognition.
Most optical character recognition (OCR) systems can
recognize at most a few scripts. But for large archives
of document images that contain different scripts,
there must be some way to automatically categorize
these documents before applying the proper OCR on
them. Much work has already been reported in this
area. In the Indian context, though some results have
been reported, the task is still at its infancy. This
paper presents a research in the identification of
Tamil, Devanagari scripts at word level irrespective
of their font faces and sizes. The proposed technique
performs document vectorization method which generates
vectors from the nine zones segmented over the characters
based on their shape, density and transition features.
Then script is proposed technique identifies scripts
with minimal pre-processing and high accuracy. It
can also be extended for other scripts. Since this
determined by using Rule based classifiers containing
set of classification rules which are raised from
the vectors. Results from experiments, simulations,
and human vision encounter that the system can act
as a plug-in, this can be embedded with OCR prior
to the recognition stage.
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