S. Prabakaran ¹, Anna Alphy ²

Affiliations
1 Department of Computer Science and Engineering, SRM University, Kattankulathur, Chennai - 603203, Tamil Nadu, IN
2 Department of Computer Science and Engineering, SRM University, Kattankulathur,Chennai - 603203, Tamil Nadu, IN

Abstract

Objectives: The core intent of this paper is to propose a dynamic recommender system(i) to endow with an enhanced understanding of the behaviors and interest of online users and (ii) to tumble information overload by providing guidance to the online users. Methods: Foraging behavior based swarm intelligence is motivated from the dynamic social behavior of swarms. It puts forward innate option for modeling dynamic online usage data. In the preset work, we mainly concentrate on the innate resemblance between Swarm Intelligence and communal behavior. The proposed WebFrieseBee algorithm is inspired from the foraging behavior of the T. biroiFriese bees and the proposed the proposed BestProphecy-annealing algorithm is used for providing recommendations to users. Findings: The proposed WebFrieseBee is motivated from the dynamic social behavior of swarms. It offers collaborative learning and has decentralized control. Moreover, it also has high exploration ability. That is, it put forward innate option for modeling dynamic online usage data. The proposed BestProphecy-annealing algorithm uses a greedy heuristic approach, for providing recommendations to users by identifying a better neighborhood for agents and gives recommendations based on the preferences of these best neighborhoods. The proposed WebFrieseBee may overcome the data redundancies existing in the repeated use of information which are inappropriate and may provide tradeoff between coverage and precision. Improvements: Our proposed dynamic recommender system surmount the grey sheep problem and new user ramp up problem in many traditional recommender systems. Our proposed dynamic recommender system was compared with Ant clustering approach. The Experimental results shows that our approach offers better quality in terms of coverage, precision and F1 Measure than the traditional Ant clustering approaches. Applications: The recommender system is very effective in increasing the utility of e-commerce by minimizing the user surfing time and overload in servers.

Keywords

Recommender Systems, Software Agents, Stimulated Annealing, Swarm Intelligence, User Profiles, Web Usage Mining.

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K. Rama Devi ¹, S. Prabakaran ¹

Affiliations
1 Department of Computer Science and Engineering, SRM University, Chennai – 603203, Tamil Nadu, IN

Abstract

Objective: Information security is one of the essential futures challenged in data transmission through wireless networks. Networks are extremely exposed to security attacks and consign a great challenge today. Methods: In this paper we propose a new DNA Symmetric Cryptographic technique that employs Mathematical formula for encryption and decryption and private key is generated from blood analysis report. After Encryption DNA codons are generated as a cipher text which is decrypted through decryption algorithm into readable text. In this method we use classical cryptographic technique of substitution method in DNA Cryptography. Findings: The algorithm is implemented in Java Platform and comparison was prepared for encryption and decryption time for different file formats. Also size of encrypted file is also compared for different files. Improvement: DNA based approach which is more immune to cryptographic attacks. DNA Cryptography is a new and potentially excellent area that enhances data security. It helps to transmit highly confidential data efficiently and securely.

Keywords

DNA Codon, Security Attacks, Symmetric Cryptography.

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S. Prabakaran ¹, Maghna Luthra ¹

Affiliations
1 Department of CSE, SRM University, Kattankulathur, Chennai - 603203, Tamil Nadu, IN

Abstract

Objectives: To propose suitable method for localizing text in images. Methods/Statistical Analysis: Many methods of text localization use techniques based on region and textures using statistical approaches. In this paper, a domain transform based method has been proposed. The proposed approach based on wavelet transform utilizes the properties of wavelet in localizing the text. Particularly, it uses wavelet energy in differentiating text region and non text region in an image. Findings: The proposed approach was applied on many bench marked images to localize the text and found effective in achieving its purpose. Many existing methods of text localization based on region and texture, need special software or complex calculations and methods. Some of these methods require the heuristic functions like threshold and other inputs. Also, some methods are suitable for small text while some of them are suitable for large text. The proposed wavelet based method for text localization works well for small as well large text. It doesn’t need any special software. It doesn’t have any input constraints like threshold. Also it is quite simple, robust and more efficient in comparison with the existing approaches. Applications: Localizing text in images contributes much in the extraction as well as retrieval of information from an image in the web. Also, it is an important step in recognizing the text present in the image.

Keywords

Text localization, Wavelet Transform, Wavelet Energy.

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