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Journal of Computer

Technology & Applications

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ISSN: 2347 - 7229

Jan-April 2014

(JoCTA)

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Industrial Tribology Machine Dynamics & Maintenance

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Indian Institute of Technology Delhi, India.

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Dr. Divakar Singh YadavDept. of Computer Science & Engineering,

Institute of Engineering and Technology UP Technical University, Lucknow, India.

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LMISTE, MCSI, India.

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and Science, Coimbatore, India.

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Sri Ramakrishna Engineering College, NGGO Colony Post, Coimbatore, India.

I take the privilege to present the hard copy compilation for the [Volume 5 Issue (1)] Journal of

Computer Technology & Applications (JoCTA). The intension of JoCTA is to create an

atmosphere that stimulates creativeness, research and growth in the area of Computer Technology

& Applications.

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

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

reviews in areas of Journal of Computer Technology & Applications 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 Computer Science and Technology.

Finally, I express my sincere gratitude and thanks to our Editorial/ Reviewer board and Authors for

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/Review 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. A Case based Practical Approach for Novel Data Transformation to Enhance Accuracy of Decision Tree Ensembles Sandeep K. Budhani, Govind Singh 1

2. Artificial Neural Network Model for Stock Market Forecasting Neelima Budhani, C. K. Jha, Sandeep K. Budhani 7

3. End-to-End Data Security for Multi-Tenant Cloud EnvironmentTushar Bhardwaj 13

4. Study on Network Load on Various Mobile Ad Hoc Network Protocols Under the Random Walk Mobility and Random Way Point Model Sitaram Gupta, Vijay Kumar 21

5. Supporting Search as you Type using Incremental Computation and Neighborhood Technique M. Karthiga, A. Anny Leema 26

6. Survey of Data Cleaning and Image Recognition using Neural Networks Raju Dara, Ch. Satyanarayana, A. Govardhan 30

ContentsJournal of Computer Technology & Applications

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

Journal of Computer Technology & Applications ISSN: 2347-7229

Volume 5, Issue 1

www.stmjournals.com

A Case based Practical Approach for Novel Data

Transformation to Enhance Accuracy of Decision

Tree Ensembles

Sandeep K. Budhani1*, Govind Singh

2

1Department of Computer Science & Engineering,

Graphic Era Hill

University, Bhimtal Campus, India 2M.Tech (CSE), Graphic Era Hill University, Bhimtal, Uttarakhand, India

Abstract If we talk about any real world situation then we can see that all the situations dramatically changes as the time passes. If we say this statement in some technical form,

concepts changes gradually. This situation is called as Concept Drift that is the core of any approach. Until we cannot get the accurate output for a given input parameter, the

concepts will concurrently change. To overcome this situation we use a programmable

approach that is Classifier Ensembles in which we combine several outputs and form a single output from several. Other thing we get about is Decision Tree that is a very

popular ensemble method because Decision Trees are unstable classifiers whose output

undergoes significant changes. Data transformation is a process by which the problem representation is changed and we have to manipulate the problems by using some useful

techniques. This paper firstly focuses on the popular ensembles methods, the overview of decision tree and uses the concept of classifier ensemble with respect to decision trees.

There are mainly two problems associated with data transformation and we have

different approaches to resolve these problems. In this paper we consider a single novel transformation method to resolve these problems.

Keywords: Ensemble, decision trees, data, transformation method

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

Journal of Computer Technology & Applications ISSN: 2347-7229

Volume 5, Issue 1

www.stmjournals.com

Artificial Neural Network Model for Stock

Market Forecasting

Neelima Budhani1*, C. K. Jha

2, Sandeep K. Budhani

3

1Amrapali Institute, Haldwani (Nainital), Uttarakhand, India

2Banasthali Vidyapeeth, Banasthali, Rajasthan, India

3Graphic Era Hill University, Bhimtal Campus, Bhimtal (Nainital), Uttarakhand, India

Abstract In recent years, many attempts have been made to predict the behavior of bonds,

currencies, stocks or stock markets. Neural networks, as an intelligent data mining

method, have been used in many different challenging pattern recognition problems such

as stock market prediction. The aim of this paper is to predict stock market using artificial neural networks (ANNs). The authors used feed forward neural network trained

by back-propagation algorithm to make prediction. The result from analysis shows that

ANNs offer the ability to predict the stock prices more accurately than other existing techniques.

Keywords: Artificial neural network, back-propagation, forecasting, stock market

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

Journal of Computer Technology & Applications ISSN: 2347-7229

Volume 5, Issue 1

www.stmjournals.com

End-to-End Data Security for Multi-Tenant

Cloud Environment

Tushar Bhardwaj* Master of Technology, Uttar Pradesh Technical University, India

Abstract This paper details the construction of a functional model that ensures data kept encrypted; while being processed in a multi-tenanted cloud environment. This can be

done using homomorphic encryption only though the approach lacks in ability to search

large databases. In a multi-tenant cloud environment, data is stored on several distinct data centers. As the request is encrypted, the server can't come up with exact match, so it

would probably return information of all its matching records. This research work uses a functional gloved-box model that ensures an effective end-to-end cloud data security. The

outcome is that a database in the cloud be able to handle a request and return a response

without decrypting the query and data. To make things happen this way, data is first-most encrypted by using Homomorphic encryption(public-key), than decrypted using Garbled-

circuit(private key), and at last the private key of garbled-circuit is being made safe by

encrypting it again by Attribute-based Encryption.

Keywords: Multi-tenant cloud security, homomorphic, garbled-circuit, attribute-

based encryption.

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

Journal of Computer Technology & Applications ISSN: 2347-7229

Volume 5, Issue 1

www.stmjournals.com

Study on Network Load on Various Mobile Ad Hoc

Network Protocols Under the Random Walk Mobility and

Random Way Point Model

Sitaram Gupta*, Vijay Kumar Department of Computer Science and Engineering

Kautilya Institute of Technology and Engineering, Jaipur

Abstract Mobile ad hoc Network consists of mobile networks which create an underlying

architecture for communication without the help of traditional fixed-position routers.

MANET is group of mobile nodes which uses multi hop transmission for communication. Routing in MANET is challenging task, moreover presence of malicious nodes make the

overall network very insecure furthermore dynamic nature of moving nodes adds to the complexity Mobility of the nodes has substantial influence on the network performance.

In this Paper, we study the impact of Random Walk and Random Way Point model. We

focus on performance comparison of Proactive routing protocol by focusing on Optimized Link State Routing (OLSR) and Reactive Routing Protocol by focusing on Ad

Hoc on Demand Distance Vector (AODV) and Temporally Ordered Routing Algorithm

(TORA). The present paper reports a performance analysis of network load on three Mobile Ad Hoc Network (MANET) routing protocols under the two mobility models i.e.

Random Walk Mobility Model and Random Way Point.

Keywords: MANET, AODV, OLSR, TORA, OPNET 14.5, random walk mobility

model, random way point mobility model

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

Journal of Computer Technology & Applications ISSN: 2347-7229

Volume 5, Issue 1

www.stmjournals.com

Supporting Search as You Type using Incremental

Computation and Neighborhood Technique

M. Karthiga*, A. Anny Leema Master of Computer Applications, B S Abdur Rahman University, Chennai, India

Abstract The objective of the project is to develop the application Search-as -you-type system, used to show the results based on user query. If user enter any misspelled queries in

search engine, automatically it corrects the misspelled query in search box. In the

proposed system, concentrate on high performance to attain a speed of searching and showing the results very quickly and corrects the incorrect word. The performance of

search is accomplished by the auxiliary indexes in tables. This helps to improve performance and reduce the manual work.

Keywords: search as-you-type , database , SQL , fuzzy search

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

Journal of Computer Technology & Applications ISSN: 2347-7229

Volume 5, Issue 1

www.stmjournals.com

Survey of Data Cleaning and Image Recognition

using Neural Networks

Raju Dara*, Ch. Satyanarayana, A. Govardhan Jawaharlal Nehru Technological University, Hyderabad, Andhra Pradesh, India

Abstract This paper reviews the existing developments of data cleaning and image recognition

using neural networks. At present most of the work in image recognition is done by

using more than one method. Neural networks take the advantage and show good improvement in recognition of images. In this work, the authors have discussed their

advantages over traditional methods.

Keywords: Data cleaning, image recognition, data transformation, artificial neural

network