Journal of advanced database management & systems (vol1, issue1) by STM Journals Publication

Advanced Database Management & Systems Jan - April 2014

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Journal of Advanced Database Management & Systems Focus and Scope Covers † Systems Analysis and Design † Semantic Web and Ontology’s † Knowledge Modeling and Processing † Sensor data Management † Temporal, Spatial and High dimensional databases †

Database System and applications

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Niusvel Acosta Mendoza Researcher at Advanced Technologies Application Center (CENATAV) Cuba.

José María Luna Ariza Department of Computer Sciences and Numerical Analysis Campus Universitario de Rabanales. University of Córdoba, Spain.

Dr. H.S. Behera Asstistant Professor Dept. of Computer Science & Engineering Veer Surendra Sai University of Technology,Odisha, India.

Yahui chang Associate Professor Department of Computer Science and Engineering, National Taiwan Ocean University, Taiwan.

Dr. S. Nickolas Associate professor at National institute of technology tiruchirappalli. India.

Shaoxu Song Assistant Professor School of Software, Tsinghua University Beijing, China.

Sebastián Ventura Associate Professor Department of Computer Science and Numerical Analysis. University of Córdoba. Spain.

Jenq Haur Wang Assistant ProfessorDepartment of Computer Science and Information Engineering National Taipei University of Technology Taiwan.

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STM JOURNALS

I take the privilege to present the print version for the Volume 1 Issue (1) of Journal of Advanced Database Management & Systems. The intension of JoADMS is to create an atmosphere that stimulates creativeness, research and growth in the area of advanced database. The development and growth of the mankind is the consequence of brilliant Research done by eminent Scientists and Engineers in every field. JoADMS provides an outlet for Research findings and reviews in areas of advanced database 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 advanced database. 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/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

Journal of Advanced Database Management & Systems

Contents

1. Concept of Semantic Web and Its Indexing Mechanism Ela Kumar

2. An Implimentation on Extraction and Detection of Leak Data using Fake Tupples Gaurav Funage, Dipali H. Patil, Narendra Bhendekar, Sachin Goveas, Prashant Kadam

3. Design and Implementation of Security System for Medical Test Data Mining P.Y. Shende, Pranoti D. Mude

4. Identification of Thyroid Disease Severity using Fuzzy C-Means G. Jaya Suma, M. Nymisha, Sk. Teenaaz, S. Neelima, K. Gouri Shankar

Journal of Advanced Database Management & Systems Volume 1, Issue 1 www.stmjournals.com

Concept of Semantic Web and Its Indexing Mechanism Ela Kumar* Dean School of Information and Communication Technology, Gautam Buddha University, Noida, UP, India

Abstract The present paper discusses various aspects of Semantic web. The semantic web is a tool of retrieving information for web on the basis of semantics conveyed by keywords. The semantic web has an improved system of information storage where the meaning and associated words of a keywords are also stored. The indexing mechanism of for retrieval of information is improved than normal keyword based search. In this paper the indexing mechanism of semantic web is also discussed.

Keywords: Semantic web, synonymy, metadata, indexing mechanism, automatic knowledge sharing, search engine.

Journal of Advanced Database Management & Systems Volume 1, Issue 1 www.stmjournals.com

An Implimentation on Extraction and Detection of Leak Data using Fake Tupples Gaurav Funage*, Dipali H. Patil, Narendra Bhendekar, Sachin Goveas, Prashant Kadam JSPMâ&#x20AC;&#x2122;s Rajarshi Shahu College of Engineering, Tathwade, Pune-411033, India

Abstract Modern business activity contains the email exchange, sometimes email leakage is occurred in the company and it is widespread problem in the industry particularly in IT industry .so we study the following problem as data distributor (owner) has given sensitive data to trusted third parties called as (agents) and if that data leaked by trusted agents, particularly the leaked data is find on website also or can find out by using legal ways , we want to find out who has leaked that sensitive data. in early days for secure these sensitive data (information) Access Control Mechanism and Watermarking Technique were used, in Watermarking Technique unique code is embedded within data but it is not so useful for sensitive data. For keeping sensitive information of the company and finding out to this trusted third agent we implement this technique. This paper contains the results of Implementation of data leakage and detection of data using fake tupples.To find solution on this issue we proposed a system to find the Data leaker or identify the third party who leaks the data by using the fake Tupples.

Keywords: Data leakage, agents, fake tupples, distributor, access control mechanism, watermarking technique

Journal of Advanced Database Management & Systems Volume 1, Issue 1 www.stmjournals.com

Design and Implementation of Security System for Medical Test Data Mining P.Y. Shende1*, Pranoti D. Mude2 1

Electronics & Telecommunication Dept., DMIETR, Wardha, India 2 Computer Engineering Dept., KIT, Wardha, India

Abstract The growth of data mining process began when company data was first stored on computers, unrelenting with improvements in data access. Data mining deals with bulky database which may hold insightful information. Medical test security system is a major factor in our society especially this system is used for special purpose like inspection of many healthy man powers for a specific organization. In this project software is implement which is useful for detection of healthy man power to avoid the wrong way entry in Army, Navy and Air force i.e., Government and Non Government sector. In this system first of all candidate registration should be done in this registration candidate firstly give their home address and age. The identification of candidate with figure print saved in server computer along with generated barcode where medical tests will be performed. Keywords: MTSS, thumb, data mining (DM), knowledge discovery in database (KDD), data link library (DLL)

Journal of Advanced Database Management & Systems Volume 1, Issue 1 www.stmjournals.com

Identification of Thyroid Disease Severity using Fuzzy C-Means G. Jaya Suma1*, M. Nymisha2, Sk. Teenaaz2, S. Neelima2, K. Gouri Shankar2 1

Department of Computer Science and Engineering, JNTU Kakinada, University College of Engineering Vizianagaram, India 2 Department of information technology, JNTU Kakinada, University College of Engineering Vizianagaram, India Abstract

Clustering is a primary data description method in data mining which groupâ&#x20AC;&#x2122;s most similar data. Data clustering is one of the important problems in the fields of data mining, bio-informatics and pattern recognition. Various algorithms are used to solve this problem. This paper presents the performance analysis of k-means clustering algorithm and compares it with fuzzy C- Means (FCM) algorithm on Thyroid disease data set. We also find the accuracy of both the algorithms on Thyroid data set. Fuzzy clustering is useful to mine multi-dimensional and complex data sets, where the members have fuzzy or partial relations. Among the various techniques developed so far, fuzzy-C-Means (FCM) algorithm is the most popular one, where a partial membership is assigned to a piece of data with each of the pre-defined cluster centers. Moreover, in FCM, the cluster centers are virtual, that is, they are chosen at random and thus might be out of the data set. With in some iteration the cluster centers and membership values of the data points are updated. The FCM employs fuzzy portioning such that a point can belong to more than one group with different membership grades between 0 and 1. Using this membership we are going to determine the severity of thyroid disease in a person. Keywords: K-means, fuzzy C-means clustering, Euclidean distance, Manhattan distance, sigmoid membership, t-norms