Informatics Publishing Limited

Ananthi Sheshasaayee , D. Sumathy ¹

Affiliations
1 PG and Research Department of Computer Science, Quaid E Millath Government College for Women, Chennai - 600001, Tamil Nadu, IN

Abstract

Background: Online bank transactions are widely carried out through the mobiles and PDAs there by reducing much time and energy involved for any bank operation. All m-banking transactions are carried out through SMS communications between user mobile and bank server through wireless media exposed to lot of malware vulnerabilities. The problem of securing SMS using text steganography, within limited length 70/160 characters is investigated in this paper. One of the main objectives of this paper is selection of a text steganography technique for protecting the OTP SMS from the bank server to user mobile. Methods: In this paper a novel technique of hiding secret six-digit OTP under an innocent looking cover text is proposed. The property of the similarity of glyphs of Unicode characters is combined with frequency of occurrence of English letters is used to hide OTP. The similarities of glyphs provide invisibility and letter frequency improves the overall hiding ratio. Result: This method will help to secure OTP SMS generated by the bank server from malware Trojans along the communication channel and also hide the very presence of the secret information within the SMS. By analysing the result, there is no change in the way the cover text appears after embedding OTP. The extraction of the secret bits is also done effectively. In conclusion, this method will efficiently hide the secret bits and provides a medium level of security. It can be used to a maximum of 10-12 digits of OTP. Due to the limited size of 70 Unicode characters per SMS, the payload capacity gets affected if more.

Keywords

Letter Frequency, M-Banking, OTP SMS, Text Steganography, Unicode Glyphs

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Ananthi Sheshasaayee ¹, Hannah Vijaykumar ²

Affiliations
1 PG and Research Department of Computer Science, Quaid-e-Millath Government College for Women (Autonomous), Anna Salai, Chennai – 600002, Tamil Nadu, IN
2 Department of Computer Science, Quaid-e-Millath Government College for Women (Autonomous), Anna Salai, Chennai - 600002; Tamil Nadu, IN

Abstract

Theory of Constraints is an analytical tool. A theoretical model for identifying bottlenecks in agile software development methods namely Lean software development, Extreme Programming (XP), Scrum, and Feature Driven Development (FDD) is identified and comparitative analysis is done. Identifying bottlenecks narrows down possible issues in agile software development implementations. These practices are used as surgical tools for various development models to be deployed for software development system. This paper summarizes Targeting with TOC, Eliminating the Constraint and Elevating the Constraint with Agile Principles and Practices. Theory of Constraint is concluded as the best parameter for improvement of development model.

Keywords

Agile Software Development, Bottleneck, Extreme Programming (XP), Feature Driven Development (FDD), Lean Software Development, Scrum, Theory of Constraints (TOC)

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S. Jayalakshmi ¹, Ananthi Sheshasaayee ²

Affiliations
1 Periyar University, Salem – 636011, Tamil Nadu, IN
2 PG and Research Department of Computer Science, Quaid-e-Millath Government College for Women (Autonomous), Chennai – 600002, Tamil Nadu, IN

Abstract

In the recent year Question Answering System achieved significant progress in which Question Classification is an essential component. To design a question classification that assign a semantic category to a given question that represents the type of answer required resulting in an accurate Answer. In this paper present various question classification approaches and techniques, Most of the researches are used to combine Syntactic, Lexical and Semantic features are used to reduce the misclassification. These three techniques are used to improve the efficiency of the question classifications. The existing classifier lacks in accuracy, especially in fine class classification, from the various existing researches are practiced Machine Learning is the best methodology to evaluate the question classification in an appropriate way.

Keywords

Machine Learning, Question Classification, Semantic Similarity, Syntactic Features

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Ananthi Sheshasaayee ¹, V. Vidyapriya ¹

Affiliations
1 PG and Research Department of Computer Science, Quaid-E-Millath Government College for Women (A), Chennai- 600002, Tamil Nadu, IN

Abstract

Background/Objectives: Web Usage Mining (WUM) is one of the categories of web mining that identifies user patterns of web data, with the help of knowledge acquires from web logs. Methods/Statistical Analysis: The structure of the web site has to be reorganised to suit the user requirements to facilitate the user for the required pages with less page access delay. The Splay trees are efficient balanced trees when total running time is the measure of interest. Findings: The motive of mining is to find users’ access models automatically and quickly from the vast Web log data, like frequently accessed pages and time spent on those pages. Web usage mining consist of three phases namely Data pre-processing, Pattern discovery and Pattern analysis. Pre-processing tasks are used to translate unprocessed log files which are composed from web server into structured log file data. Pre-processed log file data are used for further process of web usage mining. This paper present the pre-processing technique and an approach for re-organisation of website based on the access frequency of web pages using splay tree structure. Application/Improvements: The nodes of the splay tree can be added with the information about priority of recently accessed web pages to reduce the page access delay.

Keywords

Pre Processing, Splay Tree, Web Log, Web Site Reorganisation, Web usage Mining

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H. Jayamangala ¹, Ananthi Sheshasaayee ²

Affiliations
1 Periyar University, Salem – 636001, Tamil Nadu, IN
2 PG and Research Department of Computer Science, Quaid-e-Millath Government College for Women (Autonomous), Chennai – 600002, Tamil Nadu, IN

Abstract

A major research problem in online social network is Influential node identification which has large number of ties in the network. Influence maximization finds an influential node and maximizes information diffusion. Organizations started to use information diffusion feature in marketing to improve their product promotion. To achieve influence maximization approximation algorithms and diffusion models are widely used. The existing methods consider degree and structure of the network in influential node identification. Most of the existing works consider number of nearest neighbors, user’s connectivity based on user’s rating. Influential nodes are mainly used in marketing and also used in various applications such as public opinion, healthcare, communication, education, agriculture, and epidemiology.

Keywords

Influence Maximization, Influential Node, Social Networks

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Ananthi Sheshasaayee ¹, T. A. Swetha Margaret ¹

Affiliations
1 PG and Research Department of Computer Science and Application, Quaid-E-Millath Government College for Women (Autonomous), Chennai – 600002, Tamil Nadu, IN

Abstract

Background/Objectives: Cloud technology is one of the trending acquisitions by IT industry and cloud organizations. Though it comes with numerous challenges and cost barriers, it is still considered to be an important source of commercial analytics. Methods/Statistical Analysis: Cloud combines itself with facets available in the organizations. Necessarily it doesn't seek for technical domains but matches with all available resources. Business Intelligences is a wonder source that enhances itself with cloud terminology and technical nuances of cloud resources. Response time and aspects of business intelligence solutions goes hand in hand. This paper gives a clear understanding and deep insights on mathematical indicators of Business Intelligence (BI) and its encounters with cloud lexicons. Findings: This study analyses the crucial challenges that accompanies cloud technology when utilized with business intelligence. Major contribution lies around the crucial uncertainties that overrule the opportunities in cloud computing. Mathematical analyses like return on investment and payback value methods which are used to determine the economic hand-outs and proportions towards the obtainable tenets are also deliberated in this work. Agility is measured in terms of the potential users that bypass cloud resources through business intelligence. The study also encompasses various Business intelligence chauffeurs. Applications/Improvements: The concept of BI can be well handled through cloud tools like CloudSim, CloudAnalyst and Aneka using different models of cloud. The results can be improvised with the capability of BI methods.

Keywords

Business Intelligence (BI), Capital Expenses, Response Time, Return on Investment, Service Allocator.

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Ananthi Sheshasaayee ¹, R. Jayanthi ¹

Affiliations
1 PG and Research Department of Computer Science, Quaid-E-Millath Government College for Women (Autonomous), Chennai - 600002, Tamil Nadu, IN

Abstract

Background/Objectives: To extract and interpret public opinion from informal description of text in social media websites. Methods: The informal descriptions containing opinions are Tokenized, Parts of Speech Tagging, Word-sense Disambiguation and Text Transformation/Attribute Generation are employed. Sample data pertaining to performance rating of cricket players was collected from twitter, cricinfo and cricbuzz. The reviews were rated against subjective evaluation criteria, the scale ranging from poor, moderate, good, excellent and the linguistic variables were converted into numerical values using fuzzy since the expressed opinions may be easy to understand. Findings: Opinions enhance any decision making process, so the influence of opinions from sample data pertaining to performance rating of cricket players are classified as poor, moderate, good and excellent. Application/Improvements: Using the proposed approach a generic prototype can be built that can be used to extract opinions and interpret.

Keywords

Information Extraction, Opinion Mining, Unstructured Text.

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Ananthi Sheshasaayee ¹, C. Jasmine ¹

Affiliations
1 PG and Research Department of Computer Science, Quaid-E-Millath Government College for Women, Chennai - 600002, Tamil Nadu, IN

Abstract

Background/Objectives: The major objective of this work is to increase the retrieval accuracy of medical images by measuring the visual similarity of Content-Based Image Retrieval (CBIR) system. Methods/Statistical Analysis: This paper presents an On-line Multiple Kernel Similarity (OMKS) learning framework for performing classification based on kernel-based proximity functions. In accordance with many existing methods some other related issues are also discussed and retrieval performance evaluation of the existing and proposed OMKS learning strategy is also discussed. Findings: Several number of the distance based learning algorithm has been proposed in recent works. It is mainly aimed for the sake of measuring the visual similarity corresponding to the images. This paper involves in providing a comprehensive review of the technical achievements of distance learning, machine learning along with kernel learning methods for conducting visual similarity search. The methods cited have limitation in their capability of the similar measurement with complicated patterns in most practical applications. Similarity of multimodal data identified through the multiple resources²⁸, cannot be handled. Application/Improvements: Evaluation of the technique proposed for CBIR is performed on a huge amount of image data sets where motivating results indicate that OMKS performs better than the state-of the- art techniques significantly. At last, based on OMKS technology and the rise of requisitions from practical-world applications, and idealistic future research directions have been identified as suggestions²⁹.

Keywords

Content-Based Image Retrieval (CBIR), Machine Learning Methods, Multiple Kernel Learning (MKL), Online Learning, Similarity Search.

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S. Sumitra ¹, Ananthi Sheshasaayee ²

Affiliations
1 Bharathiar University, Coimbatore, IN
2 Dept.of Computer Science Quaid, E- Millath Government College for Women(Autonomous) Anna Salai, Chennai – 600 002, IN

Abstract

This paper focus on an algorithm for identifying the quality contact lens material in the field of ophthalmology. The algorithm was generated by using Fuzzy Expert System. Contact lenses such as RGP, Soft and Hybrid are considered as the dataset for this research. An algorithm has been proposed to provide a unified model in the field of contact lens manufacturing and quality control unit. This algorithm identifies and reduces the impact of side effects on wearing the contact lens. The algorithm was designed using Fuzzy logic and implemented in Java. The logic of the algorithm focuses on identifying the appropriate contact lens, which can be used as a second opinion tool for the opticians, ophthalmologist and optometrists.

Keywords

Contact Lens, Expert System, Fuzzy Logic, Opticians, Ophthalmologist.

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