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Articles by S. Prabakaran
Total Records ( 4 ) for S. Prabakaran
  Anna Alphy and S. Prabakaran
  Rapid development of computer technology allows as accessing huge amount online information’s. Next e-Business requirement will be personalizing or customizing the web pages according to the requirement of individuals. Personalization involves learning user’s navigational behavior. Web personalization uses web usage mining techniques to customize the web pages. The web usage mining uses data mining techniques to discover interesting usage patterns from web data. The web pages having similar usage pattern are clustered. As users increases or growth in interest of users the size of the cluster increases and it will become inevitable need to optimize clusters. This study proposes a cluster optimizing methodology based on honey bees foraging behavior and is used for eliminating the data redundancies that may occur after the clustering done by web usage mining methods. Genetic clustering is used for the process of clustering. “WebBEE approach for cluster optimization” is presented to personalize web pages for target users.
  N. Karthikeyan , S. Manikandan , M. Ganesh Kumar and S. Prabakaran
  Metal oxide materials are widely used as sensing material. Experimental studies have been conducted to explore the potential of fine metal oxide powders obtained by stirred bead milling for sensing of oxygen towards the thin film technique. Though the results indicate the potential of these materials for sensing, further optimization with respect to milling parameters and pelletizing are required to develop these as sensor materials.
  T. Senthil Kumar and S. Prabakaran
  In wireless mobile network, during handoff technique, authentication is required in order to transfer the information in secured way. Hence, in this study, we propose a privacy preserving handoff authentication protocol for wireless mobile networks. In this protocol, Attribute Based Signature (ABS) is applied for handoff authentication between the mobile node (UE) and the BS. The attributes considered are pseudo id of the UE, time slot and location information. Whenever, the UE decides to handoff to a selected BS it signs the message using its attribute List L and the Secret Key (SK) and transmit to BS. The BS verifies the signature and generates a blind signature which is transmitted to the UE. UE verifies the blind signature and creates the Session Key (SK) for that slot. By simulation results, we show that the proposed technique enhances the network security.
  R. Shanthi and S. Prabakaran
  Automatic and accurate localization of Optic Disk and Cup (ODC) in retinal fundus image is a necessary process for diagnosis of glaucoma. Glaucoma is the second leading chronic eye disorder which harms the optic nerve head and causes vision loss which leads to permanent blindness. The glaucoma can be detected by segmenting ODC boundary and calculating the Ratio of optic Disc and Cup (CDR). This study presents an effective framework for automatic segmentation of ODC boundary. The framework begins with median filtering to smoothen the original fundus image, followed by region of interest is marked, next superpixel is generated using SLIC method, finally, Hough transform circle and Otsu’s threshold method is used to detect the optic disc and cup boundary. Drive online public dataset is used to assess the performance of the proposed system. The average precision, recall and F-score values obtained for detecting optic disc are 0.98, 0.97 and 0.95, respectively and for optic cup a precision, recall and F-score values are 0.92, 0.95 and 0.93, respectively. The experiment results achieved is showed that the proposed technique gives better result in segmenting the boundary of optic disc and cup in retinal fundus image.
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