Recent Trends in

Programming Languages

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Jan - April 2014

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Recent Trends in Programming Languages

Focus and Scope Covers

† High - Level programming languages

† Data Representation, Data Abstraction, Procedure activation

† Programming Language C

† IF- - THEN - ELSE, SWITCH, WHILE, FOR, DO

† Parameter passing, Pointers, Arrays, Structures, C-Library

† Program transformation techniques

† Debugging for functional languages

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Industrial Tribology Machine Dynamics & Maintenance

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Indian Institute of Technology Delhi, India.

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Alternative Energy Technology Laboratory,

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National Institute Of Technology Karnataka, Surathkal, PO Srinivasnagar

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Dr. Nilam Assistant Professor Delhi Technological

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I take the privilege to present the print version for the [Volume 1 Issue (1)] of Recent Trends in

Programming Languages. The intension of RTPL is to create an atmosphere that stimulates

creativeness, research and growth in the area of Programming Languages.

The development and growth of the mankind is the consequence of brilliant Research done by

eminent Scientists and Engineers in every field. RTPL provides an outlet for Research findings and

reviews in areas of Programming Languages found to be relevant for National and International

recent developments & research initiative.

The aim and scope of the Journal is to provide an academic medium and an important reference for

the advancement and dissemination of Research results that support high level learning, teaching and

research in the domain of Programming Languages.

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their continued support and invaluable contributions and suggestions in the form of authoring write

ups/ reviewing and providing constructive comments for the advancement of the journals. With

regards to their due continuous support and co-operation, we have been able to publish quality

Research/Reviews findings for our customers base.

I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra

Director

STM Journals

Director's Desk

STM JOURNALS

1. TextSum: An Automatic Text Summarization Tool using Bayesian Classification G. Rohini, P. Krishna Subba Rao, Ch. Avinash 1

2. Multiple Sequence Alignment Algorithms for a Protein Structure for a Biological Data using Dynamic Programming Method P. V. S. Lakshmi Jagadamba 4

ContentsRecent Trends in Programming Languages

RTPL (2014) © STM Journals 2014. All Rights Reserved

Recent Trends in Programming Languages

Volume 1, Issue 1

www.stmjournals.com

TextSum: An Automatic Text Summarization Tool using

Bayesian Classification

G. Rohini, P. Krishna Subba Rao*, Ch. Avinash

Department of Computer Science and Engineering, Gayatri Vidya Parishad College

of Engineering Visakhapatnam, India

Abstract Automatic text summarization is the process of summarizing text from one or more documents in order to help the reader to determine if [s]he has to read the document(s)

in full. Although automatic summarization is around for many years, there is a renewed

interest in this area from the government, industry, and academia. The reason is the availability of large quantities of information due to world wide web and the necessity to

summarize such information. Automatic summarization involves reducing text

document(s) into shorter form which conveys the same meaning as the original documents. Summarization may be done by extractive methods or abstractive methods.

This paper consists of an Automatic Text Summarization Tool which takes into account several features, including sentence position, positive and negative key words, sentence

centrality etc., and employs the Bayesian classification algorithm to identify the

sentences that are to be included in the summary.

Keywords: Automatic text summarization, bayesian classification

RTPL (2014) © STM Journals 2014. All Rights Reserved

Recent Trends in Programming Languages

Volume 1, Issue 1

www.stmjournals.com

Multiple Sequence Alignment Algorithms for a Protein

Structure for a Biological Data using Dynamic

Programming Method

P. V. S. Lakshmi Jagadamba* Department of Computer Science Engineering School of Engineering, G.V.P. College

for Degree and P.G Courses, Technical Campus

Abstract Many algorithms use dynamic programming to align two sequences. In this paper a new

algorithm is proposed to perform multiple Sequence alignment. This algorithm is

developed by taking the inspiration of dynamic programming and is implemented on protein structures of any length. It uses particle swarm optimization (PSO) techniques to

get the best alignment. The proposed approach tries to improve the sequence alignment obtained by Needleman Wunsch algorithm.

Keywords: Dynamic Programming, Pair wise Alignment, Particle Swarm

Optimization, Machine Learning.