Using concept similarity in cross ontology for adaptive e-Learning systems

Abstracte-Learning is one of the most preferred media of learning by the learners. The learners search the web to gather knowledge about a particular topic from the information in the repositories. Retrieval of relevant materials from a domain can be easily implemented if the information is organized and related in some way. Ontologies are a key concept that helps us to relate information for providing the more relevant lessons to the learner. This paper proposes an adaptive e-Learning system, which generates a user specific e-Learning content by comparing the concepts with more than one system using similarity measures. A cross ontology measure is defined, which consists of fuzzy domain ontology as the primary ontology and the domain expert’s ontology as the secondary ontology, for the comparison process. A personalized document is provided to the user with a user profile, which includes the data obtained from the processing of the proposed method under a User score, which is obtained through the user evaluation. The results of the proposed e-Learning system under the designed cross ontology similarity measure show a significant increase in performance and accuracy under different conditions. The assessment of the comparative analysis, showed the difference in performance of our proposed method over other methods. Based on the assessment results it is proved that the proposed approach is effective over other methods

A Graph theory algorithmic approach to data clustering and its Application

Clustering is the unproven classification of data items, into groups known as clusters. The clustering problem has been discussed in many area of research   in many disciplines; this reflects its huge usefulness in the field of data analysis. However, clustering may be a difficult problem statistically, and the differences in assumptions in different disciplines made concepts and methodologies slow to occur. This paperpresentstaxonomy of clustering techniques, and recent advances in graphtheorytic approach. We also describe some important applications of clustering algorithms such as image segmentation, object recognition, and information retrieval

Stable Route Link in on-Demand Multicast Routing Protocol for Ad Hoc Networks

AbstractMobile ad hoc networks (MANET) are provisionally connected networks with no permanent infrastructure. A mobile ad hoc network is a self-organized and energetically reconfigurable wireless network without wired infrastructure and central administration. Nodes in the mobile ad hoc network can immediately create a communication structure while each node moves in a random way. Multicasting is capable of performing required services for ad hoc applications. The dynamic nature of the network topology and limited resources, maintaining and finding the path for multicasting data is still further challenging. Several protocols have been designed for multicasting in mobile ad hoc networks. On demand multicast routing protocol is one such protocol. ODMRP is mesh based and on-demand protocol that uses forwarding group to communicate a mesh for each multicasting group. The aim of the proposed algorithm is to find the stable path selection in ODMRP for forwarding packets. The basic on demand multicast routing protocol path selection uses minimum delay principle. The proposed algorithm considers node energy in path selection from source to destination. This article discusses the studies on output parameters such as control overhead and end to end delay by varying the input parameters viz., multicast groups size and mobility in the developed algorithm. Experimental results confirm that this approach can improve stability of path due to node energy consumption

Multi-oriented text detection in scene images

10.1142/S0218001412550105International Journal of Pattern Recognition and Artificial Intelligence267IJPI

A new run length based method for scene text detection

Proceedings of the 5th Indian International Conference on Artificial Intelligence, IICAI 20111730-173